About

Since its inception in 2017, the Machine Learning and the Physical Sciences (ML4PS) workshop has served as a unique gathering space for the growing community spearheading cross-cutting research topics at the intersection of machine learning (ML) and the physical sciences (PS). This includes the applications of ML to problems in the physical sciences (ML for PS) as well as developments in ML motivated by physical insights (PS for ML). The physical sciences are defined inclusively, including but not limited to physics, astronomy, cosmology, chemistry, biophysics, materials science, and Earth science.

The physical sciences pose challenging, high-profile questions that invite innovation and opportunities for cross-pollination between ML researchers and physical scientists. Recent years have seen a tremendous increase in cases where ML models are used for scientific inference and discovery (e.g., geometric deep learning, simulation-based inference), and simultaneously tools and insights from the physical sciences have been used to develop efficient ML models (e.g., diffusion models and physics-informed neural networks). The communities coalescing at this workshop are encouraged to pursue fresh, synergistic solutions to "big science" questions that can spark new approaches in ML.

This year's programming explores the evolving interplay between academia and industry in basic research. Invited talks and panel discussions emphasize the myriad foundational and translational connections between these domains. Furthermore, we ask: how can our community help sustain open, curiosity-driven research in physics and related sciences when traditional funding models are under strain? What role can industry play in supporting fundamental science, and how can the insights emerging from basic research in the physical sciences and ML help catalyze wider innovations in industry and beyond?

NeurIPS 2025

The Machine Learning and the Physical Sciences 2025 workshop will be held on December 6, 2025 at the San Diego Convention Center in San Diego, Californa (USA) as a part of the 39th annual conference on Neural Information Processing Systems (NeurIPS). The workshop is planned to take place in a hybrid format inclusive of virtual participation.

Schedule

All times are local, i.e. Pacific Standard Time (PST). See also the official NeurIPS workshop schedule.

8:15am - 8:30am Opening remarks
8:30am - 9:15am Invited talk: Michael Albergo
9:15am - 10:00am Invited talk: Tess Smidt
10:00am - 10:30am Coffee break
10:30am - 10:45am Paper spotlight: Ming-Shau Liu
"Continuous Representations of Baryonic Feedback for Robust Inference from Multiple Simulation Suites"
10:45am - 11:00am Paper spotlight: Kshitij Duraphe
"The Platonic Universe: Do Foundation Models See the Same Sky?"
11:00am - 12:00pm Poster session #1
12:00pm - 1:00pm Lunch break
1:00pm - 2:00pm Panel Discussion: How should we translate ML advances between academia & industry?
Exploring the interplay of academia & industry using weather and climate research as a case study.
Panelists: Anima Anandkumar, Peter Harrington, and Laure Zanna
2:00pm - 2:15pm Paper spotlight: Zichun Hao
"RINO: Renormalization Group Invariance with No Labels "
2:15pm - 2:30pm Paper spotlight: Malachi Schram
"Continual Learning for Particle Accelerators "
2:30pm - 3:30pm Poster session #2
3:30pm - 4:00pm Coffee break
4:00pm - 5:00pm Panel Discussion: What could the "AlphaFold moment" be for fundamental physics?
A conversation on paradigm-shifting applications across ML and particle/astro/accelerator physics.
 Panelists: Auralee Edelen, Shirley Ho, Jascha Sohl-Dickstein, and Daniel Whiteson

Job Postings

Are you hiring? Send your job ad to ml4ps@googlegroups.com and we will add it to our spreadsheet:

Plenary Speakers

Panelists

Panel Discussion: How should we translate ML advances between academia & industry?
Exploring the interplay of academia & industry using weather and climate research as a case study.
Panel Discussion: What could the "AlphaFold moment" be for fundamental physics?
A conversation on paradigm-shifting applications across ML and particle/astro/accelerator physics.

Papers

Accepted papers are listed below.

2 DiffICF : Diffusion-Driven Inverse Modeling for Laser Pulse Design in Inertial Confinement Fusion (MLPS) [paper] [poster]
Ricardo Luna Gutierrez, Vineet Gundecha, Rahman Ejaz, Varchas Gopalaswamy, Riccardo Betti, Sahand Ghorbanpour, Aarne Lees, Soumyendu Sarkar
5 Tensorization of neural networks for improved privacy and interpretability [paper] [poster]
José Ramón Pareja Monturiol, Alejandro Pozas-Kerstjens, David Perez-Garcia
6 Physics-constrained Plane Wave Decomposition Network: Solving the Helmholtz Equation in Airborne Acoustics [paper] [poster]
James Hipperson, Trevor J. Cox, Jonathan Andrew Hargreaves
7 Embedding conservation structure in neural fields for reduced state dynamics modeling from sparse and noisy measurements [paper] [poster]
Aviral Prakash, Ben S. Southworth, Marc Louis Klasky
8 Latent Target Score Matching, with an application to Simulation-Based Inference [paper] [poster]
Joohwan Ko, Tomas Geffner
9 Adaptive Online Emulation for Accelerating Complex Physical Simulations [paper] [poster]
Tara Tahseen, Nikolaos Nikolaou, Luís F. Simões, Kai Hou Yip, Joao Manuel Mendonca, Ingo P. Waldmann
12 OptICF: Sample-Efficient Optimization of Implosion Outcomes in Inertial Confinement Fusion [paper] [poster]
Ricardo Luna Gutierrez, Vineet Gundecha, Rahman Ejaz, Varchas Gopalaswamy, Riccardo Betti, Sahand Ghorbanpour, Aarne Lees, Soumyendu Sarkar
13 Deceptron: Learned Local Inverses for Fast and Stable Physics Inversion [paper] [poster]
Aaditya L. Kachhadiya
14 Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems [paper] [poster]
Quercus Hernández, Max Win, Thomas C. O'Connor, Paulo Arratia, Nathaniel Trask
15 Scaling Laws and Pathologies of Single-Layer PINNs: Network Width and PDE Nonlinearity [paper] [poster]
Faris Chaudhry
16 Real-Time Neuromorphic Spectrum Intelligence Simulator [paper] [poster]
Navaneetha Krishnan K
17 Physics-Informed Neural Controlled Differential Equations for Long Horizon Multi-Agent Motion Forecasting [paper] [poster]
Shounak Sural, Charles Kekeh, Wenliang Liu, Federico Pecora, Mouhacine Benosman
19 Geometric Operator Learning with Optimal Transport [paper] [poster]
Xinyi Li, Zongyi Li, Nikola Borislavov Kovachki, Anima Anandkumar
20 Test-time Scaling Techniques in Theoretical Physics - A Comparison of Methods on the TPBench Dataset [paper] [poster]
Zhiqi Gao, Tianyi Li, Yurii Kvasiuk, Sai Chaitanya Tadepalli, Daniel J. H. Chung, Maja Rudolph, Frederic Sala, Moritz Münchmeyer
21 Spacier: A Dataset for Modeling Electrostatic Poisson–Boltzmann Atomic Solvation Potentials [paper] [poster]
Yongxian Wu, Ray Luo
22 Meta-Learning Fourier Neural Operators for Hessian Inversion and Enhanced Variational Data Assimilation [paper] [poster]
Hamidreza Moazzami, Asma Jamali, Nicholas Kevlahan, Rodrigo Vargas-Hernandez
23 Principled Operator Learning in Ocean Dynamics: The Role of Temporal Structure [paper] [poster]
Vahidreza Jahanmard, Ali Ramezani-Kebrya, Robinson Hordoir
24 A Neural Universal Differential Equation (UDE) Approach for Modeling and Forecasting NIFTY 50 Index (Indian Stock Market Index) Prices and Drifts [paper] [poster]
Ishaan Prasad Kulkarni
25 PhysiX: A Foundation Model for Physics Simulations [paper] [poster]
Tung Nguyen, Arsh Koneru, Shufan Li, Aditya Grover
27 Smooth and Sparse Latent Dynamics in Operator Learning with Jerk Regularization [paper] [poster]
Xiaoyu Xie, Saviz Mowlavi, Mouhacine Benosman
28 SeasonCast: A Masked Latent Diffusion Model for Skillful Subseasonal-to-Seasonal Prediction [paper] [poster]
Tung Nguyen, Tuan Pham, Troy Arcomano, Rao Kotamarthi, Ian Foster, Sandeep Madireddy, Aditya Grover
32 Radio Astronomy in the Era of Vision-Language Models: Prompt Sensitivity and Adaptation [paper] [poster]
Mariia Drozdova, Erica Lastufka, Vitaliy Kinakh, Taras Holotyak, Daniel Schaerer, Slava Voloshynovskiy
33 Generative Neural Networks for Kerr Combs [paper] [poster]
Janet Zhong, Eran Lustig, Shiye Su, Louise Schul, Jamison Sloan, Congyue Deng, Jelena Vuckovic, Shanhui Fan
34 Universal Spectral Tokenization via Self-Supervised Panchromatic Representation Learning [paper] [poster]
Jeff Shen, Francois Lanusse, Liam Holden Parker, Ollie Liu, Tom Hehir, Leopoldo Sarra, Lucas Thibaut Meyer, Micah Bowles, Sebastian Wagner-Carena, Helen Qu, Siavash Golkar, Alberto Bietti, Hatim Bourfoune, Pierre Cornette, Keiya Hirashima, Geraud Krawezik, Ruben Ohana, Nicholas Lourie, Michael McCabe, Rudy Morel, Payel Mukhopadhyay, Mariel Pettee, Kyunghyun Cho, Miles Cranmer, Shirley Ho
35 FlowTIE: Flow-based Transport of Intensity Equation for Phase Gradient Estimation from 4D-STEM Data [paper] [poster]
Arya Bangun, Maximilian Töllner, Xuan Zhao, Christian Kuebel, Hanno Scharr
37 Differentiable Interference Modeling for Cost-Effective Growth Estimation of Thin Films [paper] [poster]
Leonard Storcks, Gunnar Ehlers, Robin Janssen, Konrad Storcks, Tayebeh Ameri, Tobias Buck
38 Direct Molecular Polarizability Prediction with $\boldsymbol{SO(3)}$ Equivariant Local Frame GNNs [paper] [poster]
Jean Philip Filling, Michael Wand, Denis Andrienko, Felix Post
39 Physics-Informed Inverse Design of Optical Coatings using a Differentiable Transfer Matrix Method [paper] [poster]
Utsa Chattopadhyay, Florian Carstens, Morten Steinecke, Andreas Wienke, Ingmar Hartl, Nihat Ay, Christoph M Heyl, Henrik Tünnermann
40 Neural Field Turing Machine: A Differentiable Spatial Computer [paper] [poster]
Akash Malhotra, Nacera seghouani
41 A Bio-Inspired Hierarchical Temporal Defense for Securing Spiking Neural Networks Against Physical and Adversarial Perturbations [paper] [poster] [video]
Sylvester Kaczmarek
44 Blind Strong Gravitational Lensing Inversion: Joint Inference of Source and Lens Mass with Score-Based Models [paper] [poster]
Gabriel Missael Barco, Ronan Legin, Connor Stone, Yashar Hezaveh, Laurence Perreault-Levasseur
45 Sequential decoder training for improved latent space dynamics identification [paper] [poster]
William Anderson, Youngsoo Choi, Seung Whan Chung
47 Rollout-LaSDI: Enhancing the long-term accuracy of Latent Space Dynamics. [paper] [poster]
Robert Stephany, Youngsoo Choi
48 FALCON: An ML Framework for Fully Automated Layout-Constrained Analog Circuit Design [paper] [poster]
Asal Mehradfar, Xuzhe Zhao, Yilun Huang, Emir Ceyani, Yankai Yang, Shihao han, Hamidreza Aghasi, Salman Avestimehr
50 Quantum Boltzmann Machines for Sample-Efficient Reinforcement Learning [paper] [poster]
Thore Gerlach, Michael Schenk, Verena Kain
53 ASTROCO: Self-Supervised Conformer-Style Transformers for Light-Curve Embeddings [paper] [poster]
Antony Tan, Pavlos Protopapas, Martina Cádiz-Leyton, Guillermo Cabrera-Vives, Cristobal Donoso-Oliva, Ignacio Becker
54 Neuromorphic Random Walk for Experimental Phosphate Adsorption Modeling [paper] [poster]
Rodrigo P. Ferreira, Rui Ding, Rapti Ghosh, Haihui Pu, Junhong Chen
56 From Black Hole to Galaxy: Neural Operator Framework for Accretion and Feedback Dynamics [paper] [poster]
Nihaal Bhojwani, Chuwei Wang, Hai-Yang Wang, Chang Sun, Elias R Most, Anima Anandkumar
57 Robustness by Design: Interface Contracts for AI Control in High-Stakes Physical Systems [paper] [poster]
Vacslav Glukhov, Georgy Subbotin, Maxim Nurgaliev
59 Learning IRC-Safe Jet Clustering with Geometric Algebra Transformers [paper] [poster]
Gregor Kržmanc, Roberto Seidita, Annapaola de Cosa
60 PI-NAV: Physics-Informed Universal Differential Equations for Enhanced Nanorobot Navigation through Complex Bio-environments [paper] [poster]
Tarushri N. S., Prathamesh Dinesh Joshi, Raj Dandekar, Rajat Dandekar, Sreedath Panat
61 Differentiable Models for Control of Complex Physical Systems: A Case Study in Laser Pulse Shaping [paper] [poster]
Denis Ilia, Nihat Ay, Ingmar Hartl, Wolfgang Hillert, Henrik Tünnermann
62 Power Ensemble Aggregation for Improved Extreme Event AI Prediction [paper] [poster]
Julien Collard, Pierre Gentine, Tian Zheng
63 SoDaDE: Solvent Data-Driven Embeddings with Small Transformer Models [paper] [poster]
Gabriel Kitso Gibberd, Jose Pablo Folch, Antonio Del rio chanona
64 Learning Solution Operators for Partial Differential Equations via Monte Carlo-Type Approximation [paper] [poster]
Salah Eddine Choutri, Prajwal Chauhan, Othmane Mazhar, Saif Jabari
65 GLOW: A Unified Particle Flow Transformer [paper] [poster]
Dmitrii Kobylianskii, Samuel Van Stroud, Kwok Yiu Wong, Max Hart, Etienne Dreyer, Eilam Gross, Gabriel Facini, Tim Scanlon
66 Topology-Agnostic Event Reconstruction with Hierarchical Graph Neural Networks [paper] [poster]
Nathalie Soybelman, Francesco Armando DI Bello, Nilotpal Kakati, Eilam Gross
67 Hybrid Physical-Neural Simulator for Fast Cosmological Hydrodynamics [paper] [poster]
Arne Thomsen, Tilman Tröster, Francois Lanusse
68 PIANO: Physics-informed Dual Neural Operator for Precipitation Nowcasting [paper] [poster]
Seokhyun Chin, Junghwan Park, Woojin Cho
69 Lagrangian neural ODEs: Measuring the existence of a Lagrangian with Helmholtz metrics [paper] [poster]
Luca Wolf, Tobias Buck, Bjoern Malte Schaefer
70 An Evaluation of Representation Learning Methods in Particle Physics Foundation Models [paper] [poster]
Michael Chen, Raghav Kansal, Abhijith Gandrakota, Zichun Hao, Ngadiuba Jennifer, Maria Spiropulu
71 Caffarelli Regularity and Hierarchical Phase Boundaries in Diffusion Model Latent Space [paper] [poster]
Alexander Lobashev, Dmitry Guskov, Victor Kawasaki-Borruat, Maria Larchenko
72 Denoising weak lensing mass maps with diffusion model and generative adversarial network [paper] [poster]
Shohei D. Aoyama, Ken Osato, Masato Shirasaki
75 Fourier Neural Operators for Fast Simulation and Inverse Design of Second-Harmonic Generation in TFLN Waveguide [paper] [poster]
Valentin Duruisseaux, Robert M. Gray, Siyuan Jiang, Selina Zhou, Robert Joseph George, Kamyar Azizzadenesheli, Alireza Marandi, Anima Anandkumar
76 Sub-microsecond Transformers for Jet Tagging on FPGAs [paper] [poster]
Lauri Laatu, Chang Sun, Arianna Cox, Abhijith Gandrakota, Benedikt Maier, Ngadiuba Jennifer, Zhiqiang Que, Wayne Luk, Maria Spiropulu, Alexander Tapper
77 Inverse Design with Fourier Neural Operators for Quantum System Control [paper] [poster]
Anastasia Pipi, G. Nivedha, Valentin Duruisseaux, Myrl G Marmarelis, Taylor Lee Patti, Brucek Khailany, Prineha Narang, Anima Anandkumar
80 JaxWildfire - A GPU-Accelerated Wildfire Simulator for Reinforcement Learning [paper] [poster]
Ufuk Çakır, Victor-Alexandru Darvariu, Bruno Lacerda, Nick Hawes
81 RINO: Renormalization Group Invariance with No Labels [paper] [poster]
Zichun Hao, Raghav Kansal, Abhijith Gandrakota, Chang Sun, Ngadiuba Jennifer, Javier Duarte, Maria Spiropulu
82 ComptonINR: Implicit Neural Representations for Fast Modeling of Compton Telescope Point Spread Functions [paper] [poster]
Anirudh Kotamraju, Andreas Zoglauer
83 Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics [paper] [poster]
Nima Sedaghat, Tanawan Chatchadanoraset, Colin Orion Chandler, Ashish Mahabal, Maryam Eslami
85 Learning Drosophila ventral furrow formation with graph neural networks [paper] [poster]
Shaoxun Huang, Haiqian Yang, Hyuntae Jeong, Xinran O Zhao, Ian Y. Wong, Markus Buehler, Adam C Martin, Ming Guo
87 The Platonic Universe: Do Foundation Models See the Same Sky? [paper] [poster]
Kshitij Duraphe, Michael J. Smith, Shashwat Sourav, John F Wu
88 A Preliminary Study into the Conceptual Design of Aircraft using Simulation-Based Inference [paper] [poster]
Aurelien Ghiglino, Daniel Elenius, Anirban Roy, Ramneet Kaur, Manoj Acharya, Colin Samplawski, Brian Matejek, Susmit Jha, Juan Alonso, Adam D. Cobb
89 AutoHood3D: A Multi‑Modal Benchmark for Automotive Hood Design and Fluid–Structure Interaction [paper] [poster]
Vansh Sharma, Harish Jai Ganesh, Maryam Akram, Wanjiao Liu, Venkat Raman
91 Enforcing governing equation constraints in neural PDE solvers via training-free projections [paper] [poster]
Omer Rochman-Sharabi, Gilles Louppe
92 Latent Nonlinear Wave Dynamics in Image Datasets and Autoencoder Reconstructions [paper] [poster]
Alexey Yermakov, Lillian J. Ratliff, J. Nathan Kutz
93 Agentic AI at the Advanced Light Source [paper] [poster]
Thorsten Hellert, João Montenegro, Antonin Sulc
96 AdaptFNO: Adaptive Fourier Neural Operator with Dynamic Spectral Modes and Multiscale Learning for Climate Modeling [paper] [poster]
Hiep V. Dang, Bach Nguyen, Phong C.H. Nguyen, Truong-Son Hy
98 Capturing Long-Range Intramolecular Interactions with TDiMS for Interpretable Property Prediction [paper] [poster]
Lisa Hamada, Akihiro Kishimoto, Junta Fuchiwaki, Kohei Miyaguchi, Indra Priyadarsini, Hirose Masataka, Seiji Takeda, Sina Klampt, Takao Moriyama
99 Learning Quantum Data Distribution via Chaotic Quantum Diffusion Model [paper] [poster]
Quoc Hoan Tran, Koki Chinzei, Yasuhiro Endo, Hirotaka Oshima
100 P-DRUM: Post-hoc Descriptor-based Residual Uncertainty Modeling for Machine Learning Potentials [paper] [poster]
Shih-Peng Huang, Nontawat Charoenphakdee, Yuta Tsuboi, Yong-Bin Zhuang, Wenwen Li
102 LINKER: Learning Interactions Between Functional Groups and Residues With Chemical Knowledge-Enhanced Reasoning and Explainability [paper] [poster]
PhucPhamHuyThien, Viet Thanh Duy Nguyen, Truong-Son Hy
103 Granularity Beyond Hardware: Super-Resolution for Enhanced Particle Reconstruction in Calorimeters [paper] [poster]
Nilotpal Kakati, Etienne Dreyer, Eilam Gross
104 Reasoning With a Star: A Heliophysics Dataset and Benchmark for Agentic Scientific Reasoning [paper] [poster]
Kevin Lee, Russell Spiewak, James Walsh
105 SR-Traffic: Discovering Macroscopic Traffic Flow Models with Symbolic Regression [paper] [poster]
Simone Manti, Saeed Mohammadian, Martin Treiber, Alessandro Lucantonio
107 TeBaAb: Text-Based Antigen-Conditioned Antibody Redesign via Directed Evolution [paper] [poster]
Cuong Manh Nguyen, Huy-Hoang Do-Huu, Viet Thanh Duy Nguyen, Truong-Son Hy
108 Squeezed Diffusion Models [paper] [poster]
Jyotirmai Singh, Samar Khanna, James Burgess
110 Reliable Parameter Inference for the Epoch of Reionization using Balanced Neural Ratio Estimation [paper] [poster]
Diego González-Hernández, Molly Wolfson, Joseph Hennawi
111 Benchmarking of Neural Operator for rigid-body fluid-structure interaction [paper] [poster]
Weiheng Zhong, Hadi Meidani
112 Learning Data-Efficient and Generalizable Neural Operators via Fundamental Physics Knowledge [paper] [poster]
Siying Ma, Mehrdad Momeni Zadeh, Mauricio Soroco, Wuyang Chen, Jiguo Cao, Vijay Ganesh
114 Mars-Bench: A Benchmark for Evaluating Foundation Models for Mars Science Tasks [paper] [poster]
Mirali Purohit, Bimal Gajera, Vatsal Malaviya, Irish Mehta, Kunal Sunil Kasodekar, Jacob Adler, Steven Lu, Umaa Rebbapragada, Hannah Kerner
115 Physics–Preference Aligned Tool-Using Policies for Molecular Design with Gemma-3 270M [paper] [poster]
Daoyuan Li
116 Adaptive Neural Quantum States: A Recurrent Neural Network Perspective [paper] [poster] [video]
Jake McNaughton, Mohamed Hibat-Allah
117 Physics-aware Discrete Reparameterization with Symmetry-aware Bayesian Fusion for Multimodal Radiography [paper] [poster]
Nga Nguyen-Fotiadis, Bradley T. Wolfe, David P Broughton, Zhehui Wang, Nathan A. Debardeleben, Earl Lawrence
118 EquiHGNN: Scalable Rotationally Equivariant Hypergraph Neural Networks [paper] [poster]
Tien Dang, Truong-Son Hy
120 Physics-Informed Neural Networks for Modeling Galactic Gravitational Potentials [paper] [poster]
Charlotte Myers, Nathaniel Starkman, Lina Necib
123 Mechanism discovery with thermodynamically consistent and atom conserving chemical reaction neural networks [paper] [poster]
Felix Döppel, Mauro Bracconi, Matteo Maestri
125 Learning Pairwise Potentials via Differentiable Recurrent Dynamics [paper] [poster]
Kenji Komiya, Andrew Kailiang Jin, Ryo Nishikimi, Kunio Kashino
126 Self-supervised Synthetic Pretraining for Inference of Stellar Mass Embedded in Dense Gas [paper] [poster]
Keiya Hirashima, Shingo Nozaki, Naoto Harada
127 Weight-sharing Transformer quantum states with Suzuki–Trotter decompositions [paper] [poster]
Kimihiro Yamazaki, Itsushi Sakata, Takuya Konishi, Yoshinobu Kawahara
128 Warping Away Nonstationarity: Benefits in Mineral Resource Estimation [paper] [poster]
Fabian Leal-Villaseca, Mark D Lindsay, Edward Cripps, Mark Jessell
129 An Empirical Investigation of Neural ODEs and Symbolic Regression for Dynamical Systems [paper] [poster]
Panayiotis Ioannou, Pietro Lio, Pietro Cicuta
131 Surrogate-Assisted PINNs with Hard Constraints for Heterogeneous Catalytic Reactor Modeling [paper] [poster]
Felix Döppel, Mauro Bracconi, Matteo Maestri
132 Predicting symbolic ODEs from multiple trajectories [paper] [poster]
Yakup Emre Şahin, Niki Kilbertus, Sören Becker
134 Differentiable Physics-Neural Models enable Learning of Non-Markovian Closures for Accelerated Coarse-Grained Physics Simulations [paper] [poster]
Tingkai Xue, Chin Chun Ooi, Zhengwei Ge, Fong Yew Leong, LI Hongying, Chang Wei Kang
135 Unsupervised Discovery of High-Redshift Galaxy Populations with Variational Autoencoders [paper] [poster]
Aayush Saxena
137 Fast PINN Eigensolvers via Biconvex Reformulation [paper] [poster]
Akshay Sai Banderwaar, Abhishek Gupta
140 Spectroscopic Completeness and Photometric Redshift Performance in Astronomical Foundation Models [paper] [poster]
Andrew William Engel, Hailey Widger, Annika Peter, Peter Taylor
142 Transfer Learning Beyond the Standard Model [paper] [poster]
Veena Krishnaraj, Adrian E. Bayer, Christian Kragh Jespersen, Peter Melchior
143 Exoplanet formation inference using conditional invertible neural networks [paper] [poster]
Remo Burn, Hubert Klahr, Victor F. Ksoll
144 Galactification: painting galaxies onto dark matter only simulations using a transformer-based model [paper] [poster]
Shivam Pandey, Christopher C. Lovell, Chirag Modi, Benjamin Dan Wandelt
145 Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation [paper] [poster]
Gérôme Andry, Sacha Lewin, François Rozet, Omer Rochman-Sharabi, Mangeleer Victor, Matthias Pirlet, Elise Faulx, Gilles Louppe
147 Modeling X-ray photon pile-up with a normalizing flow [paper] [poster]
Ole König, Juan Rafael Martínez-Galarza, Douglas Finkbeiner, Daniela Huppenkothen, Christian Kirsch, James F. Steiner, Joern Wilms, Justina R. Yang
148 GeoGraph: Geometric and Graph-based Ensemble Descriptors for Intrinsically Disordered Proteins [paper] [poster]
Eoin Quinn, Marco Carobene, Jean QUENTIN, Sebastien Boyer, Miguel Arbesú, Oliver Bent
151 Sampling 3D Molecular Conformers with Diffusion Transformers [paper] [poster]
Thorben Frank, Winfried Ripken, Gregor Lied, Klaus Robert Muller, Oliver T. Unke, Stefan Chmiela
153 Learning at the Speed of Physics: Equilibrium Propagation on Oscillator Ising Machines [paper] [poster]
Alex Gower
154 Flexible Gravitational-Wave Parameter Estimation with Transformers [paper] [poster]
Annalena Kofler, Maximilian Dax, Stephen R Green, Jonas Bernhard Wildberger, Nihar Gupte, Jonathan Gair, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf
155 Continual Learning for Particle Accelerators [paper] [poster]
Kishansingh Rajput, Malachi Schram, Willem Blokland, Alexander Zhukov, Sen Lin
157 Towards Universal Neural Operators through Multiphysics Pretraining [paper] [poster]
Mikhail Masliaev, Dmitry A. Gusarov, Ilya Markov, Alexander Hvatov
158 A Discrete-Continuous Curriculum Learning (DCCL) Framework for Stable Long-Horizon PDE Surrogates [paper] [poster]
Lalit Ghule, Akanksh Shetty, Morgane Bourgeois
159 Uncertainty based Online Ensemble on Non-Stationary Data for Fusion Science [paper] [poster]
Kishansingh Rajput, Sen Lin, Malachi Schram, Brian Sammuli
160 Edge Machine Learning for Cluster Counting in Next-Generation Drift Chambers [paper] [poster]
Deniz Yilmaz, Liangyu Wu, Julia Gonski
161 Multiscale stochastic parameterization with deep Mori-Zwanzig formalism [paper] [poster]
Juan Nathaniel, Carla Roesch, Jatan Buch, Kaitlyn Loftus, Daniel Giles, Derek DeSantis, Pierre Gentine
162 Transformer Embeddings for Fast Microlensing Inference [paper] [poster]
Nolan Smyth, Laurence Perreault-Levasseur, Yashar Hezaveh
167 A Benchmarking Framework for AI models in Automotive Aerodynamics [paper] [poster]
Kaustubh Tangsali, Rishikesh Ranade, Mohammad Amin Nabian, Alexey Kamenev, Peter D Sharpe, Neil Ashton, Ram Cherukuri, Sanjay Choudhry
169 Group Averaging for Physics Applications: Accuracy Improvements at Zero Training Cost [paper] [poster]
Valentino F. Foit, David W Hogg, Soledad Villar
170 SAIR: Enabling Deep Learning for Protein-Ligand Interactions with a Synthetic Structural Dataset [paper] [poster]
Pablo Lemos, Zane Beckwith, Sasaank Bandi, Jordan Crivelli-Decker, Benjamin J. Shields, Thomas Merth, Punit K Jha, Nicola De Mitri, Tiffany Callahan, Romelia Salomon-Ferrer, Martin Ganahl
172 What Machine Learning Methods is Physics invested in? [paper] [poster]
Steve Schmerler, Peter Steinbach
174 Deep Learning for Classification of Low Surface Brightness Galaxies in Dark Energy Survey [paper] [poster]
Bilguun Batbayar
176 Natural gradient descent for improving variational inference based classification of radio galaxies [paper] [poster]
Devina Mohan, Anna M M Scaife
177 Extrapolating Phase-Field Simulations in Space and Time with Purely Convolutional Architectures [paper] [poster]
Christophe Bonneville, Nathan Bieberdorf, Pieterjan Robbe, Mark Asta, Habib N. Najm, Laurent Capolungo, Cosmin Safta
178 An LLM-driven framework for cosmological model-building and exploration [paper] [poster]
Nayantara Mudur, Carolina Cuesta-Lazaro, Michael W. Toomey, Douglas Finkbeiner
179 Towards Methane Detection Onboard Satellites [paper] [poster] [video]
Maggie Chen, Hala Lamdouar, Luca Marini, Laura Martínez-Ferrer, Dr C. P. Bridges, Giacomo Acciarini
180 Knowledge is Overrated: A zero-knowledge machine learning and cryptographic hashing-based framework for verifiable, low latency inference at the LHC [paper] [poster]
Pratik Jawahar, Maurizio Pierini, Caterina Doglioni
182 Mind the Gap: Navigating Inference with Optimal Transport Maps [paper] [poster]
Malte Algren, Tobias Golling, Francesco Armando DI Bello, Chris Pollard
183 Angular Sparsity Invariant Tilt Series Generation in Scanning/Transmission Electron Microscopy [paper] [poster]
Dikshant Sagar, Zhaoxu Li, Sherif Abdelkarim, Pierre Baldi, Joseph P Patterson
184 Neural Field Transformations for Hybrid Monte Carlo: Architectural Design and Scaling [paper] [poster]
Jinchen He, Xiao-Yong Jin, James C. Osborn, Yong Zhao
185 Graph-based Neural Space Weather Forecasting [paper] [poster]
Daniel Holmberg, Ivan Zaitsev, Markku Alho, Ioanna Bouri, Fanni Franssila, Haewon Jeong, Minna Palmroth, Teemu Roos
187 Toward Complete Merger Identification at Cosmic Noon with Deep Learning [paper] [poster]
Aimee L. Schechter, Aleksandra Ciprijanovic, Rebecca Nevin, Laura Blecha, Julia Comerford, Aaron Stemo, Xuejian Shen
188 Manifold Learning for Cosmic Structures [paper] [poster]
Ana Sofia Uzsoy, Claire Lamman, Melanie Weber
189 Inverse Autoregressive Flows for Zero Degree Calorimeter fast simulation [paper] [poster]
Emilia Majerz, Witold Dzwinel, Jacek Kitowski
190 Seeing the Forest Through the Trees: Knowledge Retrieval for Streamlining Particle Physics Analysis [paper] [poster]
James McGreivy, Blaise Delaney, Anja Beck, Mike Williams
191 Uncertainty Quantification for Reduced-Order Surrogate Models Applied to Cloud Microphysics [paper] [poster]
Jonas Erno Katona, Emily Katherine de Jong, Nipun Gunawardena
192 Power law attention biases for molecular transformers [paper] [poster]
Jay Shen
194 One-Shot Transfer Learning for Nonlinear PDEs with Perturbative PINNs [paper] [poster]
Samuel Auroy, Pavlos Protopapas
195 Symbolic Regression Is All You Need: From Simulations to Scaling Laws in Binary Neutron Star Mergers [paper] [poster]
P. Darc, Clecio R. Bom, Charles Kilpatrick, Bernardo M O Fraga, Gabriel S. M. Teixeira
196 MG-NECOLA: Fast Neural Emulators for Modified Gravity Cosmologies [paper] [poster]
John Bayron Orjuela-Quintana, César Alonso Valenzuela Toledo, Elena Giusarma, Mauricio Reyes, Neerav Kaushal, Francisco Villaescusa-Navarro
197 Hybrid Attention State Space Models for Symbolic Calculation of Squared Amplitudes [paper] [poster]
Karaka Prasanth Naidu, Eric A. F. Reinhardt, Victor Baules, Nobuchika Okada, Sergei Gleyzer
198 Accelerated Blind Denoising of GPR Data via Deep Random Projections [paper] [poster]
Viven Sharma, Raunak Manekar
200 Going with the Speed of Sound: Pushing Neural Surrogates into Highly-turbulent Transonic Regimes [paper] [poster]
Léo Cotteleer, Richard Kurle, Fabian Paischer, Maurits Bleeker, Tobias Kronlachner, Johannes Brandstetter
202 Offline Maximizing Minimally Invasive Proper Orthogonal Decomposition for Reduced Order Modeling of $S_n$ Radiation Transport [paper] [poster]
Quincy Aaron Huhn, Jean C Ragusa, Youngsoo Choi
203 WaveLiT: A Parameter-Efficient Architecture for Neural PDE Solvers [paper] [poster]
Shyam Sankaran, Hanwen Wang, Paris Perdikaris
205 Diffusion-Based Electromagnetic Inverse Design of Scattering Structured Media [paper] [poster]
Mikhail Tsukerman, Konstantin Grotov, Pavel Ginzburg
206 High-resolution weak lensing mass mapping from DES-Y3 data using diffusion-based prior [paper] [poster]
Supranta Sarma Boruah, Michael Jacob, Riya Maiya, Raghav Venkataramanan, Bhuvnesh Jain
207 Simulation-based inference for neutrino interaction model parameter tuning [paper] [poster]
Karla Tame-Narvaez, Aleksandra Ciprijanovic, Steven Gardiner, Giuseppe Cerati
208 Governing Equation Discovery with Relaxed Symmetry Constraints [paper] [poster]
Andrew J Chen, Jianke Yang, Rose Yu
209 FOXES: A Framework For Operational X-ray Emission Synthesis [paper] [poster]
Griffin Goodwin, Jayant Biradar, Alison March, Christoph Schirninger, Robert Jarolim, Angelos Vourlidas
211 An Attention-Based Spatio-Temporal Neural Operator with Uncertainty Quantification for Dynamical Systems [paper] [poster]
Vispi Nevile Karkaria, Doksoo Lee, Yi-Ping Chen, Yue Yu, Wei Chen
212 DNN-based Signal Processing for Liquid Argon Time Projection Chambers [paper] [poster]
Mun Jung Jung, Gray Putnam, Haiwang Yu, Avinay Bhat
214 Heterogeneous Point Set Transformers for Segmentation of Multiple View Particle Detectors [paper] [poster]
Edgar E Robles, Dikshant Sagar, Alejandro Yankelevich, Jianming Bian, Pierre Baldi
215 The View From Space: Navigating Instrumentation Differences with EOFMs [paper] [poster]
Ryan Peter DeMilt, Nicholas LaHaye, Karis Tenneson
216 Efficient optimization of COHERENT detector design parameters with the Rare Event Surrogate Model [paper] [poster]
Brian Zhou Liu, Sonata Simonaitis-Boyd, Ann-Kathrin Schuetz, Aobo Li, Zepeng Li
217 Moment Estimates and DeepRitz Methods on Learning Diffusion Systems with Non-gradient Drifts [paper] [poster]
Fanze Kong, Chen-Chih Lai, Yubin Lu
218 Vision Transformers for Cosmological Fields: Application to Weak Lensing $\kappa$ Maps [paper] [poster]
Jash Kakadia, Shubh Agrawal, Kunhao Zhong, Bhuvnesh Jain
219 Multi-Modal Masked Autoencoders for Learning Image-Spectrum Associations for Galaxy Evolution and Cosmology [paper] [poster]
Morgan Himes, Samiksha Krishnamurthy, Andrew Lizarraga, Srinath Saikrishnan, Vikram Seenivasan, Jonathan Soriano, Ying Nian Wu, Tuan Do
220 The Pareto frontier of resilient jet tagging [paper] [poster]
Rikab Gambhir, Matt LeBlanc, Yuanchen Zhou
221 An end-to-end pipeline for uncertainty-aware validation of generative AI [paper] [poster]
Giada Badaracco, Sean Benevedes, Gaia Grosso, Christina Reissel, Thea Klaeboe Aarrestad, Philip Harris
222 In Search of the Unknown Unknowns: A Multi-Metric Distance Ensemble for Out of Distribution Anomaly Detection in Astronomical Surveys [paper] [poster]
Siddharth Chaini, federica bianco, Ashish Mahabal
223 Towards Reliable Sea Ice Drift Estimation in the Arctic: Deep Learning Optical Flow on RADARSAT-2 [paper] [poster]
Daniela Martin, Joseph Gallego
224 Revisiting Conditional Whitney Forms: From Structure Preservation to Physics Recovery [paper] [poster]
Pavlos Kallinikidis, Paris Perdikaris, George J. Pappas
225 From Descriptions to Chemical Hazards: Predicting Persistence, Bioaccumulation, and Toxicity from Natural Language Using LLMs [paper] [poster]
Sarathkrishna Swaminathan, Nathaniel H. Park, Eduardo Soares, Emilio Vital Brazil
226 Implicit Augmentation from Distributional Symmetry in Turbulence Super-Resolution [paper] [poster]
Julia Balla, Jeremiah Bailey, Ali Backour, Elyssa Hofgard, Tommi Jaakkola, Tess Smidt, Ryley McConkey
227 $\Delta$-ML Ensembles for Selecting Quantum Chemistry Methods to Compute Intermolecular Interactions [paper] [poster]
Austin Michael Wallace, Charles Sherrill, Giri P Krishnan
228 A Suitable and Interpretable Methodology for FTIR Spectral Classification [paper] [poster]
Thomas Hartigan, Tiago Azevedo, Pietro Lio
229 Biodiversity Change: A Spatiotemporal Machine Learning Approach to Detect Forest Canopy Height Changes across the U.S. West Coast [paper] [poster]
Steven Lu, Antonio Ferraz, Samuel-Hunter Berndt
230 Generation-Based Multi-Modal Anomaly Detection for Nuclear Fusion Target Polishing [paper] [poster]
Sherif Abdelkarim, Antonios Alexos, Shashank Galla, Vikash Sunkara, Kshitij Bhardwaj, Sean Hayes, Monika Biener, Satish Bukkapatnam, Pierre Baldi, Suhas Bhandarkar
232 Equivariant Compression of Quantum Operator Representations [paper] [poster]
Jigyasa Nigam, Utku Sirin, Tess Smidt, Stratos Idreos
233 Uncertainty Quantification of Seismic Imaging Using Neural Posterior Principal Components [paper] [poster]
Julia Gao, Annika Viswesh
234 From Images to Physics: Probabilistic Inference of Galaxy Parameters and Emission Lines via VAE–Normalizing Flows [paper] [poster]
Adiba Amira Siddiqa, Sayed Shafaat Mahmud, Juan Rafael Martínez-Galarza
235 Generalizing PDE Emulation with Equation-Aware Neural Operators [paper] [poster]
Qian-Ze Zhu, Paul Raccuglia, Michael Brenner
237 Learning Spatiotemporal Diffusion Models with Continuous-time PDE Guidance [paper] [poster]
Juho Latukka, Markus Heinonen, Harri Lähdesmäki
238 Why is Attention Sparse in Particle Transformer? [paper] [poster]
Aaron Wang, Timothy Legge, Jacob Ortiz, Victor Limouzi, Abhijith Gandrakota, Elham E Khoda, Zihan Zhao, Javier Duarte, Ngadiuba Jennifer, Richard Cavanaugh
239 Real-Time Anomaly Detection System for Data Quality Monitoring in the CMS ECAL using Autoencoders [paper] [poster]
Abhirami Harilal
240 High-Accuracy Neural-Network Quantum States via Randomized Real-Time Dynamics [paper] [poster]
John Michael Martyn, Di Luo
241 Transformers for Deterministic Magnetic Field Control in Particle Accelerators [paper] [poster]
Anton Lu, Verena Kain
242 Reconstructing Conformal Field Theoretical Composition with Transformers [paper] [poster]
Haotian Cao, Garrett W. Merz, Kyle Cranmer, Gary Shiu
244 Foam-Agent: A Multi-Agent Framework for Automating OpenFOAM-based CFD Simulation [paper] [poster]
Ling Yue, Nithin Somasekharan, Tingwen Zhang, Yadi Cao, Shaowu Pan
245 Reinforcement Learning for Ising Models: Datasets and Benchmark [paper] [poster]
Levy Lin, Zhiyuan Wang, Holden Mac Entee, Xingjian Zhao, Xiao-Yang Liu
246 Uncovering Physical Drivers of Dark Matter Halo Structures with Auxiliary‑Variable‑Guided Generative Models [paper] [poster]
Arkaprabha Ganguli, Anirban Samaddar, Florian Kéruzoré, Nesar Soorve Ramachandra, Julie Bessac, Sandeep Madireddy, Emil Constantinescu
247 Scalable Machine Learning Analysis of Parker Solar Probe Solar Wind Data [paper] [poster]
Daniela Martin, Connor O'Brien, Valmir P Moraes Filho, Jinsu Hong, Jasmine R. Kobayashi, Evangelia Samara, Joseph Gallego
248 Electron-Proton Scattering Event Generation using Structured Tokenization [paper] [poster]
Steven Goldenberg, Diana McSpadden, Nobuo Sato, Kostas Orginos, Robert G. Edwards
249 CIPHER: Scalable Time Series Analysis for Physical Sciences with Application to Solar Wind Phenomena [paper] [poster]
Jasmine R. Kobayashi, Daniela Martin, Valmir P Moraes Filho, Connor O'Brien, Jinsu Hong, Sudeshna Boro Saikia, Hala Lamdouar, Nathan D. Miles, Marcella Scoczynski, Mavis Stone, Sairam Sundaresan, Anna Jungbluth, Andrés Muñoz-Jaramillo, Evangelia Samara, Joseph Gallego
251 Generating Calabi-Yau manifolds with transformers [paper] [poster]
Charles Arnal, Jacky H. T. Yip, Francois Charton, Gary Shiu
252 HEAL-PINN: Physics-Informed Swin Transformer for Dark Matter Studies for Sparse Lensing Data [paper] [poster]
Dhruv Srivastava, Pranath Reddy, Michael W. Toomey, Sergei Gleyzer
253 Improving and Assessing Astronomical Light Curve Classifiers with Classification Histories [paper] [poster]
Zhuoyang Zhou, Alex I. Malz, Chad M. Schafer
254 Uncovering Solar Wind Phenomena with iSAX, HDBScan, Human-in-the-loop and PSP Observations [paper] [poster]
Valmir P Moraes Filho, Daniela Martin, Jasmine R. Kobayashi, Connor O'Brien, Jinsu Hong, Evangelia Samara, Joseph Gallego
255 High-Fidelity Reconstructions of Strong Lenses in the Data-Driven Generative Modeling Era [paper] [poster]
Ronan Legin, Connor Stone, Alexandre Adam, Gabriel Missael Barco, Laurence Perreault-Levasseur, Yashar Hezaveh
256 ClearPotential: Learning the Dust-Corrected Potential of the Milky Way Using Flows [paper] [poster]
Eric Putney, David Shih, Matthew R Buckley, Sung Hak Lim
257 Distributed Element-Local Transformer for Scalable and Consistent Mesh-Based Modeling [paper] [poster]
Shyam Sankaran, Riccardo Balin, Bethany Lusch, Shivam Barwey
258 GalaxyScore: Estimating Local Dark Matter Density in Galaxies with Score Matching [paper] [poster]
Sung Hak Lim, David Shih, Matthew R Buckley, Eric Putney
259 Multimodal Generative Flows for LHC Jets [paper] [poster]
Darius A Faroughy, Cesar Ojeda, Manfred Opper
260 Fake It Till You Make It: Multi-Physics Synthesis Breaks the Data Barrier in Chemical Language Models [paper] [poster]
Naiyu Yin, Ning Liu, Jiuzhou Chen, Brian Y. Lattimer, Jim Lua, Yue Yu
261 Developing Surrogates for Epidemic Agent-Based Models via Scientific Machine Learning [paper] [poster]
Sharv Murgai, Utkarsh Utkarsh, Kyle C. Nguyen, Alan Edelman, Erin C.S. Acquesta, Christopher Vincent Rackauckas
262 Fourier–Thermodynamic Latent Modeling for Temperature-Dependent Plasma Mixing [paper] [poster]
Jannik Eisenlohr, Youngsoo Choi, Michael Murillo
263 Diffusion Autoencoders with Perceivers for Long, Irregular and Multimodal Astronomical Sequences [paper] [poster]
Yunyi Shen, Alexander Thomas Gagliano
264 Encoding and Understanding Astrophysical Information in Large Language Model-Generated Summaries [paper] [poster]
Kiera McCormick, Juan Rafael Martínez-Galarza
265 From Simulations to Surveys: Domain Adaptation for Galaxy Observations [paper] [poster]
Kaley Brauer, Aditya Prasad Dash, Meet J. Vyas, Ahmed Salim
266 Sparse Methods for Vector Embeddings of TPC Data [paper] [poster]
Tyler Wheeler, Michelle P. Kuchera, Raghuram Ramanujan, Ryan Krupp, C Wrede, Saiprasad Ravishankar, Connor L. Cross, Hoi Yan Ian Heung, Andrew J. Jones, Benjamin Votaw
267 Anomaly Detection in Astrophysics – VAE Separates Interacting Binary Stars from Normal Red Giants [paper] [poster]
Abhigyan Acherjee, Jennifer Sokoloski, Savannah Jennifer Thais
268 Large Language Model-based Bayesian Optimization for Tokamak Stabilization [paper] [poster]
Tejus Gupta, Rohit Sonker, Efe Mert Karagözlü, Alexandre Capone, Barnabas Poczos, Jeff Schneider
270 Multi-modal Foundation Model for Cosmological Simulation Data [paper] [poster]
Bin Xia, Nesar Soorve Ramachandra, Azton Wells, Salman Habib, John Wise
271 FoamGPT: Fine-Tuning Large Language Model for Agentic Automation of CFD Simulations with OpenFOAM [paper] [poster]
Ling Yue, Peijing Xu, Tingwen Zhang, Nithin Somasekharan, Shaowu Pan
272 Combining datasets with different ground truths using Low-Rank Adaptation to generalize image-based CNN models for photometric redshift prediction [paper] [poster]
Vikram Seenivasan, Srinath Saikrishnan, Andrew Lizarraga, Jonathan Soriano, Bernie Boscoe, Tuan Do
273 Solving Inverse Problem Using Physics-Constrained Machine Learning [paper] [poster]
Junbo Peng
278 Designing Optimal Computation Protocols from Fluctuation Response Relations [paper] [poster]
Jinghao Lyu
280 Scalable Inference for LArTPC Signal Processing with MobileU-Net and Overlap–Tile Chunking [paper] [poster]
Dikshant Sagar, Edgar E Robles, Sergey Martynenko, Yiwen Xiao, Jianming Bian, Pierre Baldi, Hokyeong Nam, Jay Hyun Jo, Wenqiang Gu, Brett Viren, Haiwang Yu
281 Best of Both Worlds: Bridging Laplace and Fourier for Generalizable and Efficient Operator Learning [paper] [poster]
Jeongun Ha, Donghun Lee
282 GT-IBTR-3D: Graph Transformer for 3D Ice-Bed Topography Reconstruction [paper] [poster]
Zesheng Liu, Maryam Rahnemoonfar
283 Sparse Interpretable Deep Learning with LIES Networks for Symbolic Regression [paper] [poster]
Mansooreh Montazerin, Majd Al Aawar, Antonio Ortega, Ajitesh Srivastava
285 Symbolic Regression via Order-Invariant Embeddings and Sparse Decoding [paper] [poster]
Krish Malik, Eric A. F. Reinhardt, Victor Baules, Nobuchika Okada, Sergei Gleyzer
286 Locality-Sensitive Hashing-Based Efficient Point Transformer for Charged Particle Reconstruction [paper] [poster]
Shitij Govil, Jack P. Rodgers, Yuan-Tang Chou, Siqi Miao, Amit Saha, Advaith Anand, Kilian Lieret, Gage DeZoort, Mia Liu, Javier Duarte, Pan Li, Shih-Chieh Hsu
287 Lightweight Fourier Neural Operator for Time-Dependent Partial Differential Equations [paper] [poster]
Dawon Ahn, Satish Chandran, Daniel Leibovici, Nikola Borislavov Kovachki, Evangelos E. Papalexakis, Jean Kossaifi
292 Scalable and accurate simulations of the Hubbard model with neural quantum states [paper] [poster]
Ao Chen, Christopher Robert Roth, Zhou-Quan Wan, Anirvan M. Sengupta, Antoine Georges
293 Autonomous Pressure Control in MuVacAS via Deep Reinforcement Learning and Deep Learning Surrogate Models [paper] [poster]
Guillermo Rodríguez-Llorente, Galo Gallardo Romero, Rodrigo Morant Navascués, Nikita Khvatkin Petrovsky, Anderson S., Roberto Gómez-Espinosa Martín
296 Hierarchical Graph Networks for Forecasting Terrestrial Water Storage Anomalies [paper] [poster]
Viola Steidl, Xiao Xiang Zhu
297 Robust Halo Masses using HaloFlow with Domain Adaptation [paper] [poster]
Nikhil Garuda, Khee-Gan Lee, ChangHoon Hahn, Connor Bottrell
299 Inference of Star Formation and Metallicity Histories from Galaxy Spectra with Score-Based Models [paper] [poster]
Sacha Perry-Fagant, Connor Stone, Yashar Hezaveh, Laurence Perreault-Levasseur
300 Data-efficient U-Net for Segmentation of Carbide Microstructures in SEM Images of Steel Alloys [paper] [poster]
Alinda Ezgi Gerçek, Till Korten, Paul Chekhonin, Maleeha Hassan, Peter Steinbach
301 Double Descent and Overparametrization in Particle Physics Data [paper] [poster]
Matthias Vigl, Lukas Heinrich
303 Embedding Jets with Maximum Manifold Capacity Representations [paper] [poster]
Samuel Bright-Thonney
304 Active Learning for Machine Learning Driven Molecular Dynamics [paper] [poster]
Kevin Bachelor, Sanya Murdeshwar, Daniel Sabo, Razvan Marinescu
305 Geometry‑Aware Hemodynamics via a Transformer Encoder and Anisotropic RBF Decoder [paper] [poster]
Reza Akbarian Bafghi, Sukirt Thakur, Maziar Raissi
307 Algebraformer: A Neural Approach to Linear Systems [paper] [poster]
Pietro Sittoni, Francesco Tudisco
309 Scheduled Temporal Loss Weighting for Neural Operators [paper] [poster]
Oluwaseun Coker, Peter Kane Jimack, Amirul Khan, He Wang
310 Assimilation of Sparse Vehicle Trajectories with a Macroscopic Traffic Model [paper] [poster]
Julien Moreau, Marc Lelarge
312 Evolving graph codes with improved error thresholds for Pauli channels [paper] [poster]
Sujeet Bhalerao
313 Re-envisioning Euclid Galaxy Morphology: Identifying and Interpreting Features with Sparse Autoencoders [paper] [poster]
John F Wu, Mike Walmsley
315 What We Don't C: Representations for scientific discovery beyond VAEs. [paper] [poster]
Brian Rogers, Micah Bowles, Chris J. Lintott, Steve Croft
317 From Simulation to Survey: Benchmarking Super-Resolution for LSST-like Lensing Data [paper] [poster]
Aleksandr Duplinskii, Pranath Reddy, Michael W. Toomey, Sergei Gleyzer
318 Physics-Guided Machine Learning For Uncertainty Quantification In Turbulence Models [paper] [poster]
Minghan Chu, Weicheng Qian
319 Predictions and Corrections: Neural Predictors with Solver-based Correction for ODEs and PDEs [paper] [poster]
Reza Akbarian Bafghi, Hasitha De Silva, Joseph G. Kocheemoolayil, John L. Davenport, Sheik Dawood, Nastaran Shahmansouri, Adrian Lew, Sarah Osentoski, Hardik Kabaria, Maziar Raissi
320 TGLF-SINN: Deep Learning Surrogate Model for Accelerating Turbulent Transport Modeling in Fusion [paper] [poster]
Yadi Cao, Futian Zhang, Wesley Liu, Tom Neiser, Lawson Fuller, Brian Sammuli, Rose Yu
321 Phy-SRBench: A Physics Benchmark for Scientific Equation Discovery with Symbolic Regression [paper] [poster]
Nour Makke, Sanjay Chawla
323 Equivariant Flow Matching for Symmetry-Breaking Bifurcation Problems [paper] [poster] [video]
Fleur Hendriks, Ondřej Rokoš, Martin Doškář, M.G.D. Geers, Vlado Menkovski
324 Improving Posterior Inference of Galaxy Properties with Image-Based Conditional Flow Matching [paper] [poster]
Mikaeel Yunus, John F Wu, Benne Willem Holwerda
327 Forecasting the Ionosphere from Sparse GNSS Data with Temporal-Fusion Transformers [paper] [poster]
Giacomo Acciarini, Simone Mestici, Halil Kelebek, Linnea M. Wolniewicz, Michael Vergalla, Madhulika Guhathakurta, Umaa Rebbapragada, Bala Poduval, Atilim Gunes Baydin, Frank Soboczenski
328 Deep vs. Shallow: Benchmarking Physics-Informed Neural Architectures on the Biharmonic Equation [paper] [poster] [video]
Akshay Govind Srinivasan, Vikas Dwivedi, Balaji Srinivasan
329 MITRA: An AI Assistant for Knowledge Retrieval in Physics Collaborations [paper] [poster] [video]
Abhishikth Mallampalli, Sridhara Dasu
330 Differentiable Ray-Tracing for Optical Particle Detector Simulation [paper] [poster]
Omar Alterkait, César Jesús Valls
331 Reversing The Lens: Using Explainable AI To Understand Human Expertise [paper] [poster]
Roussel Rahman, Aashwin Ananda Mishra, Wan-Lin Hu
332 Neural Deprojection of Galaxy Stellar Mass Profiles [paper] [poster]
M. J. Yantovski-Barth, Hengyue Zhang, Nolan Smyth, Connor Stone, Yashar Hezaveh, Laurence Perreault-Levasseur, Martin Bureau
333 ColliderML: A High-Luminosity Detector Simulation Dataset for Machine Learning Benchmarks [paper] [poster]
Daniel Murnane
334 Neural Reduced Potential via Persistent Homology [paper] [poster]
Yoh-ichi Mototake
335 Investigating PDE Residual Attentions in Frequency Space for Diffusion Neural Operators [paper] [poster]
Medha Sawhney, Abhilash Neog, Mridul Khurana, Arka Daw, Anuj Karpatne
337 Neural Network for Simulating Radio Emission from Extensive Air Showers [paper] [poster]
Pranav Sampathkumar
338 Intrinsic dimension estimation for Radio Galaxy Zoo using diffusion models [paper] [poster]
Joan Font-Quer Roset, Devina Mohan, Anna M M Scaife
339 QCxAI: Parameter-Shift Saliency for Variational Quantum Classifiers [paper] [poster]
Sohum Mehta
340 Lens-JEPA: Physics Informed Joint Embedding Predictive Architecture for Gravitational Lensing [paper] [poster]
J Rishi, Pranath Reddy, Michael W. Toomey, Sergei Gleyzer
341 The Tokenization Bottleneck: How Vocabulary Extension Improves Chemistry Representation Learning in Pretrained Language Models [paper] [poster]
Prathamesh Ashok Kalamkar, Meissane Chami, Ned Letcher, Sahger Lad, Shayan Mohanty
343 Latent Representation Learning in Heavy-Ion Collisions with MaskPoint Transformer [paper] [poster]
Jingzong Zhang, Shuang Guo, Lilin Zhu, Lingxiao Wang, Guo-Liang Ma
344 Optical Diffraction-based Convolution for Semiconductor Mask Optimization [paper] [poster]
Young-Han Son, Dong-Hee Shin, Deok-Joong Lee, Hyun Jung Lee, Hyeonyeong Nam, Tae-Eui Kam
347 Split-N-Fit: A Differentiable Maximum Likelihood Fit for training neural networks and performing anomaly detection on data [paper] [poster]
Philip Harris, Andrzej Novak
348 Machine Learning Reconstruction of High-dimensional Electronic Structure from Angle-resolved Photoemission Spectroscopy [paper] [poster]
Yu Zhang, Yong Zhong, Huy Tran, Shuyi Li, Kyuho Lee, Harold Y. Hwang, Zhi-Xun Shen, Chunjing Jia
349 Reconstructing the local density field with combined convolutional and point cloud architecture [paper] [poster]
Baptiste Barthe--Gold, Nhat-Minh Nguyen, Leander Thiele
351 FlowLensing: Simulating Gravitational Lensing with Flow Matching [paper] [poster]
Hamees Sayed, Pranath Reddy, Michael W. Toomey, Sergei Gleyzer
352 Evaluation of Novel Fast Machine Learning Algorithms for Knowledge-Distillation-Based Anomaly Detection at CMS [paper] [poster]
Lino Gerlach, Abhishikth Mallampalli, Elliott Kauffman
354 A Self-Supervised Framework for Robust Multi-Modal Molecular Representation Learning [paper] [poster]
Indra Priyadarsini, Seiji Takeda, Lisa Hamada, Sina Klampt, Takao Moriyama
355 Why Can't Neural Networks Master Extrapolation ? Insights from Physical Laws [paper] [poster]
Ramzi Dakhmouche, Hossein Gorji
356 Preparing stabilizer states via path-aware reinforcement learning [paper] [poster]
Krishna Agaram, Siddhant Midha, Vikas K Garg
357 Graph Neural Networks on One- and Two-Body Integrals for Molecular Energy Prediction [paper] [poster]
Juan S. Carrasquilla-Gomez, Rodrigo Vargas-Hernandez
358 Connecting the Dots: A Machine Learning Ready Dataset for Ionospheric Forecasting Models [paper] [poster]
Linnea M. Wolniewicz, Halil Kelebek, Simone Mestici, Michael Vergalla, Giacomo Acciarini, Bala Poduval, Umaa Rebbapragada, Madhulika Guhathakurta, Atilim Gunes Baydin, Frank Soboczenski
359 Hierarchical Simulation-Based Inference of Supernova Power Sources and their Physical Properties [paper] [poster]
Edgar Perez Vidal, Alexander Thomas Gagliano, Carolina Cuesta-Lazaro
360 IonCast: A Deep Learning Framework for Forecasting Ionospheric Dynamics [paper] [poster]
Halil Kelebek, Linnea M. Wolniewicz, Michael Vergalla, Simone Mestici, Giacomo Acciarini, Bala Poduval, Umaa Rebbapragada, Madhulika Guhathakurta, Frank Soboczenski, Atilim Gunes Baydin
361 Automating High Energy Physics Data Analysis with LLM-Powered Agents [paper] [poster]
Eli Gendreau-Distler, Luc Tomas Le Pottier, Chengxi Yang, Dongwon Kim, Joshua Ho, Haichen Wang
362 Continuous Representations of Baryonic Feedback for Robust Inference from Multiple Simulation Suites [paper] [poster]
Ming-Shau Liu, Carolina Cuesta-Lazaro
365 Variational Autoencoder with Normalizing flow for X-ray spectral fitting [paper] [poster]
Fiona Redmen, Ethan Tregidga, James F. Steiner, Cecilia Garraffo
366 Surrogate Neural Architecture Codesign Package (SNAC-Pack) [paper] [poster]
Jason Weitz, Dmitri Demler, Benjamin Hawks, Nhan Tran, Javier Duarte

Program Committee (Reviewers)

We acknowledge the 491 members of the program committee for providing reviews on a very tight schedule and making this workshop possible. They are listed in alphabetical order below.

Aakash Patil, Aaron Wang, Aashwin Ananda Mishra, Abhijith Gandrakota, Abhilash Neog, Abhinanda Ranjit Punnakkal, Abhinav Sagar, Abhiroop Chatterjee, Abhishek Abhishek, Abhishek Chandra, Abhishikth Mallampalli, Aditya Sengar, Adrian Perez Galvan, Adrian Perez-Suay, Adwaita Janardhan Jadhav, Agnimitra Dasgupta, Ahmed MAZARI, Ahmed Youssef, Aishwarya Jadhav, Aizhan Akhmetzhanova, Ajay Mandyam Rangarajan, Akanksh Shetty, Akshata Kishore Moharir, Alan Aspuru-Guzik, Alessandro Lucantonio, Alex Sun, Alexander J Winkler, Alexander Migala, Alexander Thomas Gagliano, Alexandre Szenicer, Aman Desai, Aman Kumar, Ameya Daigavane, AmirEhsan Khorashadizadeh, Amit Kumar Jaiswal, Anant Wairagade, Andreas Filipp, Andreas Schachner, Andrey E Ustyuzhanin, Anindita Maiti, Ankita Shukla, Anna Dawid, Anna Jungbluth, Annalena Kofler, Antoine Wehenkel, Antonin Sulc, Arkaprabha Bhandari, Arkaprabha Ganguli, Arshad Rafiq Shaikh, Arvind Mohan, Arvind Ramanathan, Arvind Renganathan, Asal Mehradfar, Ashish Kattamuri, Ashley S Dale, Athénaïs Gautier, Atilim Gunes Baydin, Aurelien Dersy, Aviral Prakash, Ayush Prasad, Bariscan Kurtkaya, Barry M Dillon, Batuhan Koyuncu, Ben Meiring, Benjamin D Shaffer, Bharath Ramsundar, Bilal Thonnam Thodi, Biprateep Dey, Biswarup Bhattacharya, Boyu Zhang, Brecht F. Verbeken, Brian Nord, Bruno Raffin, Carolina Cuesta-Lazaro, Cenk Tüysüz, Charuleka Varadharajan, Chen Li, Chen-Nee Chuah, Cheng Soon Ong, Chi Xie, Chin Chun Ooi, Chinmaya Bhagat, Christian Glaser, Christina Reissel, Christine Allen-Blanchette, Christophe Bonneville, Christopher C. Hall, Chuhong Wang, Chuwei Wang, Claire David, Claire Suen, Conrad M Albrecht, Cristiano De Nobili, Dalei Wu, Daniel Murnane, Daniel Serino, Danielle C. Maddix, Daohan Wang, David Rousseau, Debanjan Konar, Deborah Bard, Deep Chatterjee, Deniz Ertuncay, Dhruv V Patel, Dianzhuo Wang, Digbalay Bose, Dikshant Sagar, Dilara ickecan, Dimitra Maoutsa, Dmitry Guskov, Dong Min Roh, Donghun Lee, Eduardo Soares, Edward Berman, Edward Jiang, Elena Pinetti, Elham E Khoda, Elise Özalp, Elyssa Hofgard, Emanuele Usai, Emine Kucukbenli, Engin Eren, Entao Yang, Eoin Quinn, Eric Chagnon, Fabian Gans, Fabian Ruehle, Fadoua Khmaissia, Fatih Dinc, Fatwir Sheikh Mohammed, Favour Nerrise, Felix Döppel, Fernando Romero-Lopez, Feyi Olalotiti, Finn Henry O'Shea, Floriano Tori, Foteini Dervisi, Francesco Alesiani, Francisco Villaescusa-Navarro, Franco Pellegrini, François Rozet, Gabriel Missael Barco, Gabriel Perdue, Gadi Naveh, Gaia Grosso, Gal Oren, Garrett W. Merz, Gary Shiu, George Stein, Georges Tod, Gergana V. Velikova, Gert-Jan Both, Gianni De Fabritiis, Gijs Vermariën, Gilles Louppe, Gourav Khullar, Graham Van Goffrier, Grant M. Rotskoff, Guillaume Lambard, Gérôme Andry, H H C, Haiqian Yang, Hala Lamdouar, Hao Wu, Haowei Ni, Harsh Sharma, Henning Kirschenmann, Hongkyu Yoon, Huanghao Mai, Hunor Csala, Ieva Kazlauskaite, Inbar Savoray, Indra Priyadarsini, Indranil Nayak, Irina Espejo Morales, Ishanu Chattopadhyay, Ivan Grega, Jack Collins, Jacky H. T. Yip, Jaemyoung Lee, Jasleen Dhillon, Jason McEwen, Jay Chan, Jay Taneja, Jean-Luc Fattebert, Jenna Pope, Jeongwhan Choi, Jessica Karaguesian, Jeyashree Krishnan, Jiahe Huang, Jiajing Chen, Jianan Zhou, Jianjun Hu, Jie Bu, Jihan K. Zaki, Jochen Garcke, Joe Germany, Joel Dabrowski, John F Wu, John Michael Martyn, Jonas Spinner, Jordi Tura, Jose Manuel Napoles-Duarte, Joseph Alejandro Gallego Mejia, Joshua Bloom, Joshua Isaacson, Joshua Shen Speagle, Joshua Yao-Yu Lin, Julia Gonski, Junbo Peng, Junichi Tanaka, Junze Liu, Ka Wa Ho, Kai Fukami, Kamilė Lukošiūtė, Kana Moriwaki, Karan Shah, Karla Tame-Narvaez, Katherine Fraser, Kathleen E. Hamilton, Keith Brown, Kenji Komiya, Kevin Greenman, Kiri Wagstaff, Kishansingh Rajput, Krish Desai, Kshitij Tayal, Kunal Sunil Kasodekar, Kuntal Pal, Kunvar Thaman, Kusumakumari Vanteru, Kyriakos Flouris, Kyriakos Hjikakou, Lalit Ghule, Lars Doorenbos, Laura Manduchi, Leander Thiele, Leonid Didukh, Li Yang, Lin Li, Lin Wang, Line H Clemmensen, Lingxiao Wang, Linnea M. Wolniewicz, Lipi Gupta, Liv Helen Våge, Luca Biggio, Lucas Thibaut Meyer, Ludger Paehler, Lukas Heinrich, MD SAJID, MUHAMMAD AMIN NADIM, Mai H Nguyen, Maksim Zhdanov, Mallikarjuna Tupakula, Mangeleer Victor, Manish Marwah, Manuel Morales-Alvarado, Marc Huertas-Company, Marcin Pietron, Maria Cervera, Mariano Javier de Leon Dominguez Romero, Mariel Pettee, Marimuthu Kalimuthu, Marina Meila, Marios Mattheakis, Mary Chriselda Antony Oliver, Mary Idera Salami, Matheus Schossler, Matija Medvidović, Matt L. Sampson, Matt LeBlanc, Matteo Manica, Matthia Sabatelli, Matthieu Blanke, Maurizio Pierini, Maximilian Dax, Medha Sawhney, Micah Bowles, Michael BAUERHEIM, Michael Churchill, Michael R Douglas, Michelle P. Kuchera, Mike Williams, Mikel Landajuela, Milad Ramezankhani, Milind Malshe, Minoo Jafarlou, Mirali Purohit, Miroslav Kubu, Mit Kotak, Mohamed Mehana, Mohammad Shahab Sepehri, Mohammad Sultan, Monika Malik, Mridul Khurana, Muhammad Firmansyah Kasim, Muhammad Khalid, Myungjoon Kim, Nadim Saad, Namid Stillman, Natalie Klein, Navaneetha Krishnan K, Nayantara Mudur, Neel Chatterjee, Negin Forouzesh, Nesar Soorve Ramachandra, Nick McGreivy, Nicole Hartman, Nikolaos Nikolaou, Nils Thuerey, Nischal Reddy Chandra, Nishan Srishankar, Nishant Panda, Nishant Sharma, Nolan Smyth, Nuno Carvalhais, Oleg Savchenko, Olivier Saut, Omar Alterkait, Ondrej Hovorka, Onur Kara, Othmane Rifki, Oz Amram, Ozan Gokdemir, P. Darc, Pankaj Rajak, Pao-Hsiung Chiu, Parag Mallick, Paul Atzberger, Pedro L. C. Rodrigues, Peer-timo Bremer, Pengcheng Xie, Peter McKeown, Peter Melchior, Peter Sadowski, Peter Steinbach, Phaedon Stelios Koutsourelakis, Phan Nguyen, Pietro Vischia, Pinaki Pal, Pradyun Hebbar, Praneeth reddy Amudala Puchakayala, Prathamesh Dinesh Joshi, Pratik Jawahar, Pritthijit Nath, Qiaohao Liang, Quoc Hoan Tran, Raghav Kansal, Raheem Karim Hashmani, Rahul Ghosh, Rajat Arora, Rasmus F. Ørsøe, Raunak Borker, Redouane Lguensat, Remmy Zen, Ricardo Vinuesa, Rishabh Jain, Rodrigo Vargas-Hernandez, Rohith Peddi, Ryan Hausen, Ryan-Rhys Griffiths, Saaketh Bhojanam, Sachin Alexander Reddy, Sajib Acharjee Dip, Saksham Kapoor, Sam Foreman, Sam Vinko, Sampad B Mohanty, Samuel Bright-Thonney, Sandeep Madireddy, Sanghamitra Neogi, Sankalp Gilda, Santosh Parajuli, Sarvesh Kumar Yadav, Satish Chandran, Satpreet Harcharan Singh, Sebastian Kaltenbach, Sebastian Wagner-Carena, Sebastien Fabbro, Shah Nawaz, Shahnawaz Ahmed, Shaokai Yang, Shashank Galla, Shehtab Zaman, Shixiao Liang, Shiyu Wang, Shounak Sural, Shreyas V, Shubhendu Trivedi, Siddhant Midha, Siddharth Mishra-Sharma, Simone Manti, Siu Wun Cheung, Sokratis Trifinopoulos, Soledad Villar, Somya Sharma, Soo Kyung Kim, Sreevani Jarugula, Srinadh Reddy Bhavanam, Srinandan Dasmahapatra, Stephen D. Webb, Stephen Zhang, Steven Dillmann, Sudhakar Pamidighantam, Sudip K Seal, Sui Tang, Sujeet Bhalerao, Supranta Sarma Boruah, Sylvester Kaczmarek, TAMIL ARASAN BAKTHAVATCHALAM, Taimur Muhammad Khan, Takashi Matsubara, Taniya Kapoor, Taoli Cheng, Tarun Kumar, Tarun Narayanan, Tejus Gupta, Theodota Lagouri, Thomas Beckers, Thomas Blum, Tiffany Fan, Till Korten, Tobias Buck, Tomasz Szumlak, Tomo Lazovich, Tri Nguyen, Tsuyoshi Okita, Udit Bhatia, V Ashley Villar, Vacslav Glukhov, Vahe Gharakhanyan, Vaibhavi Singh, Valentina Salvatelli, Vansh Sharma, Vanya Bannihatti Kumar, Ved G. Shah, Vinicius Mikuni, Vishal Dey, Vishal Sudam Jadhav, Vishwa Pardeshi, Vispi Nevile Karkaria, Vitus Benson, Vudtiwat Ngampruetikorn, Wei-Cheng Lee, Wenhao Lu, Wujie Wang, Xian Yeow Lee, Xiang Li, Xiangming Meng, Xiangyang Ju, Xiao-Yong Jin, Xiaohan Yang, Xiaolong Li, Xinyan Li, Yang Liu, Yang Xu, Yangzesheng Sun, Yannik Glaser, Yao Fehlis, Yasin Bakis, Yifan Liu, Yilin Chen, Yin Li, Yingdong Lu, Yingheng Tang, Yingtao Luo, Yiran Wang, Yitian Sun, Yixiao Kang, Yiyi Tao, Yizhi Shen, Yolanne Yi Ran Lee, Youngsoo Choi, Youngwoo Cho, Yu Wang, Yuan-Tang Chou, Yukun Song, Yunxuan Li, Yunyi Shen, Yushang Zhao, ZUKANG YANG, Zefang Liu, Zesheng Liu, Zhong Chen, Zhuo Chen, Zihan Zhu, Zineb Sordo, Zixi Hu, Zixing Song, Zixuan Wang

Call for papers

This workshop brings together physical scientists and machine learning researchers who work at the intersection of these fields by:

  • applying machine learning to problems in the physical sciences -- physics, chemistry, astronomy, earth science, biophysics, and related sciences; and
  • using physical insights to understand and/or improve machine learning techniques, for instance building hybrid machine learning algorithms that leverage physical models with machine learning blocks to create interpretable and accurate predictive models.

Accepted contributions will be presented during in-person poster sessions during the workshop. Authors will also have the opportunity to upload an optional short video summary alongside their accepted paper on our website. Selected contributions will be offered 15-minute spotlight talks. We will highlight a small number of submissions containing exceptionally well-documented code and reproducible workflows with a Reproducibility Badge.

Sign up to volunteer as a reviewer: Our community’s success relies on our reviewers – we need you! Please help us ensure a high quality program by registering to review a few papers. Follow this link to nominate yourself and let us know how many papers you would be able to review.

Important dates

  • Submission Deadline: Friday, Aug 29, 2025, 23:59 AoE
  • Author (accept/reject) notification: Monday, Sept 22, 2025, 23:59 AoE
  • Registration support application deadline: October 24, 2025, 23:59 AoE
  • Camera-ready paper and poster deadline: November 14, 2025, 23:59 AoE
  • Workshop: December 6, 2025

Submission tracks

    1. Research: We invite contributions on either completed or high-quality work-in-progress original research in the following areas:

    • ML for Physics: Innovative applications of machine learning to the physical sciences; Machine learning model interpretability for obtaining insights into physical systems; Automating/accelerating elements of the scientific process (experimental design, data collection, statistical analysis, etc.).
    • Physics in ML: Strategies for incorporating scientific knowledge or methods into machine learning models and algorithms; Applications of physical science methods and processes to understand, model, and improve machine learning models and algorithms.
    • Other areas: Any other area related to the subject of the workshop, including but not limited to probabilistic methods that are relevant to physical systems, such as deep generative models, scientific foundation models, probabilistic programming, simulation-based inference, variational inference, causal inference, etc.
    2. Datasets & Benchmarks: We invite contributions describing a dataset and/or corresponding benchmarks at the intersection of ML and Physical Sciences, in particular showcasing the unique nature of physical datasets and forward models in the context of ML applications.

    3. Perspectives: We invite researchers to present compelling and grounded viewpoints on recent directions and open questions at the intersection of ML and Physical Sciences. This track encourages perspectives on past, present, or future challenges that can stimulate productive and respectful conversations on timely topics that will benefit from the ML4PS workshop's attendees' input. Papers should meet standard scientific rigor, including using evidence and reasoning to support claims, including relevant background and context, and attributing others' work via appropriate citations.

Submission instructions

Submissions should be short papers up to 4 pages in length (excluding references).

Full submission guidelines

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Organizers

For questions and comments, please contact us at ml4ps@googlegroups.com.

Steering Committee

Team Members

Sponsors

Location

NeurIPS 2025 will take place at the San Diego Convention Center, 111 Harbor Dr, San Diego, CA 92101, United States.