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arXivPhysics-informed ML & PDEs

PDE-JEPA: Predictive Representation Learning of Latent Dynamics Modeling for Parametric PDEs

PDE-JEPA introduces predictive masked-latent pretraining with geometry projection and structured latent predictors for parametric PDE dynamics, reducing errors by 33.4% in-distribution and 51.4% on unseen parameters.

Zhentao Tan, Jianrong Zhang, Ruijie Quan, Yi Yang

Published Sep 28, 2026 · 0 citations · ▲ 53 on Hugging Face · Code ★ 9

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NeurIPS 2026U BarcelonaGoogle Deepmind / HarvardPhysics-informed ML & PDEs

Generalizable Physics Simulation through Compositional Energy Minimization

Alexandru Oarga, Yilun Du

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Massachusetts Institute of TechnPhysics-informed ML & PDEs

GLOBE: Accurate Surrogates for Boundary-Driven PDEs via Domain-Inspired Architectures and Equivariance

Peter Sharpe

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026The University of Electro-CommunPhysics-informed ML & PDEs

Sliced Wasserstein Meets Quantum Optics: Provable Wavefunctions Tomography with Scarce Noisy Measurements

Takahiro Kajisa

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Koreakorea universityPhysics-informed ML & PDEs

Gauge-Symmetric Dual Lagrangian Frameworks for Born-Oppenheimer Molecular Dynamics

Sungwoo Park, Jongwon Lee, Jiwoong Kim, Hyung-sik Yoon

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026TsinghuaPrincetonPhysics-informed ML & PDEs

Discovering Phase Space Structure in Learned Hamiltonian Systems

Jiayin Liu, Yulong Yang, Vineet Bansal, Christine Allen-Blanchette

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Fujitsu Research of AmericaFujitsu Research and DevelopmentPhysics-informed ML & PDEs

NeuralBES: A Differentiable, Control-Aware Emulator for Scalable Building Energy Modeling

Ting-Yu Dai, Takuya Kurihana, Wing Yee Au, YUNG WONG

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U OxfordPhysics-informed ML & PDEs

Trajectory-Consistent Dropout for Uncertainty Decomposition in Hamiltonian Neural Networks

Stephen J Roberts, Yuki Tachibana

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Exponent Inc.Physics-informed ML & PDEs

Train on the Sphere, Deploy on the Hill: Closed-Form-Anchored Surrogates for Real-Terrain Boundary-Integral Equations

Stephane Zsoldos, Therice Morris, Varundev Sukhil, Benjamin Wetherfield

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Los Alamos National LaboratoryPhysics-informed ML & PDEs

Foundation Models for Particle Accelerators

Mahindra Rautela, Alexander Scheinker

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026HunanTsinghua University, TsinghuaChangsha University of Science aPhysics-informed ML & PDEs

GEMS-3D: A Large-Scale 3D Gravity, Electrical, Magnetic, and Seismic Earth Simulation Dataset for Multimodal Geophysical Learning

Yonghao Wang, Meijia Huang, Wenkai Lu, Zhuo Jia and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SemyungPhysics-informed ML & PDEs

PINNBench: A Benchmark and Evaluation Study of Training Policy Selection in Hybrid PINN-Operator Solvers

Suan Lee, Namhyeon Kim, Dongmin Jin

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026KoreaPhysics-informed ML & PDEs

Symplectic Parallel Scan: A Neural Hamiltonian Framework for Accelerated Scientific Simulation

Sungwoo Park

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U Science and Technology of ChinHunanPhysics-informed ML & PDEs

PI-EDG: Physics-Informed Full-Space Electron Density Generation from Molecular Geometry

Jiahang Shen, Hongxin Xiang, Zhixiang Cheng, Keke Chen and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026PrincetonPhysics-informed ML & PDEs

Frequency-Structured Hamiltonian Neural Network for Multi-Timescale Dynamics

Yaojun Li, Yulong Yang, Christine Allen-Blanchette

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SLAC National Accelerator LaboraUniversity College London, UniveTechnische Universität MünchenUCLHumboldt Universität BerlinPhysics-informed ML & PDEs

Neural Scaling Laws in Particle Jets

Matthias Vigl, Nikita Pond, Nicole Hartman, Jackson Barr and 10 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SichuanPhysics-informed ML & PDEs

ALETHEIA: A Multi-Frequency Eddy Current Pulsed Thermography Dataset for Neural Operator Learning in Nondestructive Testing

Changbin Sun, Xiaojie, Xiaotian Chen, Yuankai Wu

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026NorthwesternNorthwestern University, NorthweU FloridaPhysics-informed ML & PDEs

Axiomatic World Modeling for Physics Reasoning

Xinye Yang, Zhenyang Liu, Yuxuan Wang, Yuanyuan Lei

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026AXXX, Institute of Numerical MatNorth-Eastern FederalLaboratory of Computational InteThe Chinese University of Hong KInstitute of Numerical MathematiPhysics-informed ML & PDEs

Transolver-GMsFEM: A Hybrid Framework for High-Contrast Multiscale PDEs on Irregular Grids

Alexander Rudikov, Sergei Stepanov, Vladimir Fanaskov, Eric Chung and 2 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026SpotlightU CambridgePrincetonPhysics-informed ML & PDEs

Learning Discrete Riemannian Metrics for Physical Fields with Cochain-Frame Equivariance

Dongzhe Zheng, Christine Allen-Blanchette

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026LMU MunichTU MunichMarburguniversityPhysics-informed ML & PDEs

Conformal Prediction for Time-Dependent PDEs

Joshua Stiller, Annika Schneider, Eyke Hüllermeier

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Korea Institute for Advanced StuMITKAISTPhysics-informed ML & PDEs

Variational Monte Carlo for Quantum Excited States via Nested Low-Rank Approximation

Minchan Jeong, Jongha (Jon) Ryu, Se-Young Yun, Gregory Wornell

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026ResolutionCSIRO TechnologyU MelbourneCSIROPhysics-informed ML & PDEs

Susceptibilities for Neural Networks Learning from Physical Data

Rohan Hitchcock, Gary W Delaney, Jonathan H Manton, Richard Scalzo and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026N2TPNanyang TechnologicalB0Labs, N2TP TechnologyN2TP Technology Solutions JSCPosts & Telecommunications IPhysics-informed ML & PDEs

SympFNO: Structure-Preserving Fourier Neural Operators for Physical Surrogate Modeling

Luong Doan, Duc H Nguyen, Khanh N Quoc, Phan Quoc Hung Mai and 6 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Chinese university of HongkongThe Chinese University of Hong KPhysics-informed ML & PDEs

Neural Operator-based Curriculum Learning for Physics-Informed Neural Networks

Lingshi MENG, Haosen Shi, Sinno Pan

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Washington StateHanoi University of Science and U Texas at AustinPennsylvania StateWashington State University, PulPhysics-informed ML & PDEs

CoupledFlow: One-Step Neural Operators for Coupled Multi-Physics PDEs

Trong Khiem Tran, Long M Bui, Phi Le Nguyen, Mrinal K Sen and 3 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Fujian University of TechnologyShenzhen Institutes of Advanced Shenzhen Institutes of Advanced Physics-informed ML & PDEs

DNS-Calibrated Local Stochastic Transition Closure for PDE-Free Long-Horizon Turbulence Diffusion

Zhuoer Lin, Wenwu He, Congcong Liu, Zhuo-Xu Cui

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026ETH ZurichETHZIBM Research EuropeSwiss Federal Institute of TechnPhysics-informed ML & PDEs

Phaedra: Learning High-Fidelity Discrete Tokenization for the Physical Sciences

Levi Lingsch, Georgios Kissas, Johannes Jakubik, Siddhartha Mishra

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Gran Sasso Science InstituteThe University of EdinburghPhysics-informed ML & PDEs

Simplifying Transformer-Based U-Net Neural Physics Simulators

Pietro Sittoni, Francesco Tudisco

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026OralShanghai Jiao TongShanghai JiaotongPhysics-informed ML & PDEs

DIAGNO: Diagonal Spherical Neural Operators for Heterogeneous Earth Dynamics Modeling

Herui Li, Bin Lu, Haonan Qi, Lei Zhou and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Colorado School of MinesNayantaPhysics-informed ML & PDEs

KerONet: A Single Softmax Readout Suffices for Physics-Informed Operator Learning

Seth Dale, Carolyn Koh, Dinesh Mehta

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026CaltechCalifornia Institute of TechnoloMITMassachusetts Institute of TechnU WashingtonPhysics-informed ML & PDEs

CFC26: Building Evaluations for Deployment in Sonar-Based Fish Counting

Madison Van Horn, Suzanne Stathatos, Sevan Brodjian, Justin Kay and 5 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026National University of Defense TPekingNorthwest PolytechnicalHong Kong PolytechnicTiangongPhysics-informed ML & PDEs

Architecture-Embedded Physics Priors for Mitigating Spectral Bias in Physics-Informed Neural Networks

Zhuo Zhang, Li Zhang, Ying Miao, Hongzong LI and 3 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Texas TechPhysics-informed ML & PDEs

Stop Quantum Machine Learning; do AI-for-Quantum instead

ziqing Guo, Ziwen Pan

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Université de Bretagne SudUniversité Bretagne SudPhysics-informed ML & PDEs

BESS-Bench: Benchmarking Spectral Representations for Be-Star Variability

Matthieu Le Lain, Sébastien Lefèvre

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Purdue, PurduePhysics-informed ML & PDEs

A Locality-Aware Surrogate for Natural-Gradient Descent in Quantum Optimization

Md Mobasshir Arshed Naved, Wenbo Xie, Wojciech Szpankowski, Ananth Grama

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Indian Institute of ScienceIndian Institute of Science, IndPhysics-informed ML & PDEs

Adaptive multiscale operator correction via learned spectral subspace and physics-informed optimization.

Subham Patel, Himanshu Pandey, RATIKANTA BEHERA

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Massachusetts Institute of TechnMITHarvardNew YorkInstituto de Astrofisica De CanaPhysics-informed ML & PDEs

Learning What's Real: Disentangling Signals and Measurement Artifacts in Multi-Sensor Data, with Applications to Astrophysics

Pablo Mercader-Perez, Carolina Cuesta Lazaro, Daniel Muthukrishna, Jeroen Audenaert and 4 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SuwonThe University of SuwonLinyiPhysics-informed ML & PDEs

MANGO:Multi-Angle Neural Gated Operators for Chirp-Perturbed PDEs

Yunlong Zhu, Zunwei Fu, Zheng Wang, EUN-HU KIM

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Institute of Computing Technolog, Chinese Academy of SciencesU Chinese Academy of ScienceInsititute of Computing TechnoloPhysics-informed ML & PDEs

Verigrad: Verification-Driven Multi-Agent GPU Kernel Generation for High-Order MLIP Derivatives

yao liu, Yuanchang Zhou, Hongtao Xu, Mingzhen Li

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
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