Physics-Informed ML papers, 2023–2026

Key findings

• Physics-Informed ML went from 50 papers in 2023 to 199 in 2026, roughly 4.0x in three years.
• NeurIPS publishes the most Physics-Informed ML work: 167 papers from 2023 to 2026, 35% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 0 in 2023 to 11 in 2026.
• Among the 5 topics under Climate and Physical Sciences, it ranks #1 by 2026 paper count; the fastest grower in the group, Weather Forecasting, is up 6.1x versus 4.0x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Derivative-Informed Training of Neural Operators On-the-Fly via Sketched Tangent Consistency
• ICML 2026Bias-Spectrum Neural Processes for Parametric PDEs: Architecture Priors Meet PDE Constraints
• ICLR 2026CONSIGN: Conformal Segmentation Informed by Spatial Groupings via Decomposition
• CVPR 2026Domain Sensitive Federated Learning with Fisher-Informed Pruning
• NeurIPS 2025Activation-Informed Merging of Large Language Models
• ICML 2025Geometry-Informed Neural Networks
• ICLR 2025Beyond the convexity assumption: Realistic tabular data generation under quantifier-free real linear constraints
• CVPR 2025A Physics-Informed Blur Learning Framework for Imaging Systems
• NeurIPS 2024ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction
• ICML 2024A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction
• ICLR 2024AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction
• CVPR 2024A Physics-informed Low-rank Deep Neural Network for Blind and Universal Lens Aberration Correction
• NeurIPS 2023ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation
• ICML 2023Gradient Descent Finds the Global Optima of Two-Layer Physics-Informed Neural Networks
• ICLR 2023Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients
• CVPR 20233D Human Pose Estimation via Intuitive Physics
• NeurIPS 2026Neural Modal Decomposition: Architectural Priors from Observables
• ICML 2026Fine-to-Coarse Fairness-Informed Multi-View Clustering
• ICLR 2026From Neural Networks to Logical Theories: The Correspondence between Fibring Modal Logics and Fibring Neural Networks
• CVPR 2026LaDy Lagrangian-Dynamic Informed Network for Skeleton-based Action Segmentation via Spatial-Temporal

All Physics-Informed ML papers

102 papers, page 1 of 3

1. ICML 2026A Deep Learning Model of Mental Rotation Informed by Interactive VR Experiments
2. ICML 2026A Geometric Lens on Physics-Aligned Data Compression
3. ICML 2026A model of errors in transformers
4. ICML 2026APIC: Orthogonalized Neuro-Symbolic Modeling for Nonlinear Dissipative Dynamics
5. ICML 2026AutoMat: Physics-Guided Agentic Reasoning for Solving Ill-Posed Inverse Microscopy Problems
6. ICML 2026Bias-Spectrum Neural Processes for Parametric PDEs: Architecture Priors Meet PDE Constraints
7. ICML 2026BioToken and BioFM – Biologically-Informed Tokenization Enables Accurate and Efficient Genomic Foundation Models
8. ICML 2026Bridging Dynamics and Data: A Unified Diffusion Framework for Mechanistically-Informed Epidemic Forecasting
9. ICML 2026BuildArena: A Physics-Aligned Interactive Benchmark of LLMs for Engineering Construction
10. ICML 2026Cardio-mmFlow: A Gaussian-Prior-Free Physics-Informed Flow Matching Framework for Electrocardiogram to mmWave Radar Synthesis
11. ICML 2026Deep Coupling Learning for Solving PDEs
12. ICML 2026Derivative Informed Learning of Exchange-Correlation Functionals
13. ICML 2026Discovering Scaling Exponents with Physics-Informed Müntz-Szász Networks
14. ICML 2026EqGINO: Equivariant Geometry-Informed Fourier Neural Operators for 3D PDEs
15. ICML 2026Fast kernel methods: Sobolev, physics-informed, and additive models
16. ICML 2026Fine-to-Coarse Fairness-Informed Multi-View Clustering
17. ICML 2026FlowPET: Physics-Informed Symplectic Flow Matching for Low-Count PET Reconstruction
18. ICML 2026From Statics to Dynamics: Physics-Aware Image Editing with Latent Transition Priors
19. ICML 2026GenUnfold: Rapidly Predict Protein Mechanical Unfolding Trajectory via a Physics-Guided Diffusion Model
20. ICML 2026Graph Rewiring based on Flow Alignment for Improving Fluid Simulation
21. ICML 2026Heavy-tailed Physics-Informed Neural Networks
22. ICML 2026Hermite-NGP: Gradient-Augmented Hash Encoding for Learning PDEs
23. ICML 2026HybridOM: Hybrid Physics-Based and Data-Driven Global Ocean Modeling with Efficient Regional Downscaling
24. ICML 2026Informed Asymmetric Actor-Critic: Leveraging Privileged Signals Beyond Full-State Access
25. ICML 2026KineFlow: Kinematic Second-Order Flow Matching for Time-Series Forecasting
26. ICML 2026LieStoNet: Learning Lie Symmetries from Spatiotemporal Data for Stochastic Dynamical Systems
27. ICML 2026LithoDreamer: A Physics-Informed World Model for Multi-Stage Computational Lithography
28. ICML 2026Mitigating Gradient Pathology in PINNs through Aligned Constraint
29. ICML 2026MUSA-PINN: Multi-scale Weak-form Physics-Informed Neural Networks for Fluid Flow in Complex Geometries
30. ICML 2026NeuroMamba: A Universal Spatiotemporal Module for Robust Perception in Degraded Sensory Streams
31. ICML 2026Origo: Interpretable Multi-physics PDE Foundation Model through Neural Operator Splitting
32. ICML 2026Overcoming PINNs Failure Modes In High Dimension With Low-Rank Fourier Sum
33. ICML 2026PGD-NO: A Neural Operator with Precomputed Geometry Decomposition for 3D Million-Scale Physics Simulations
34. ICML 2026Physics-informed coarsening for multigrid graph neural networks surrogates
35. ICML 2026Physics-Informed Distillation of Diffusion Models for PDE-Constrained Generation
36. ICML 2026Physics-informed Neural Operator Learning for Nonlinear Grad-Shafranov Equation
37. ICML 2026Physics-Informed Pre-training on Efficient Electron-Density Images for Organic Material Property Prediction
38. ICML 2026Physics-Informed Residual Flows
39. ICML 2026PINNfluence: Interpreting PINNs through Influence Functions
40. ICML 2026Plug-and-Play Guidance for Discrete Diffusion Models via Gradient-Informed Logit Correction
41. ICML 2026PolarDepth: Monocular Transparent Object Depth from Polar-Physics Priors
42. ICML 2026Posterior Concentration of Bayesian Physics-Informed Neural Networks for Elliptic PDEs
43. ICML 2026PRISM: Learning Realistic Depth via Physics-Grounded Noise Disentanglement with Semantic-Geometric Collaboration
44. ICML 2026Riemannian Diffusion Models on General Manifolds via Physics-Informed Neural Networks
45. ICML 2026Scalable Bayesian Inference for Nonlinear Conservation Laws
46. ICML 2026Signature-Informed Transformer for Asset Allocation
47. ICML 2026Spatiotemporal Imputation with Graph-Informed Flow Matching
48. ICML 2026Spectral-Informed Neural Networks Outperform Spectral methods in High-dimensional PDEs
49. ICML 2026Taming the Loss Landscape of PINNs with Noisy Feynman–Kac Supervision: Operator Preconditioning and Non-Asymptotic Error Bounds
50. ICML 2026TINNs: Time-Induced Neural Networks for Solving Time-Dependent PDEs

FAQ

How many Physics-Informed ML papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

481 in total: 50 in 2023, 85 in 2024, 147 in 2025, 199 in 2026.

How many Physics-Informed ML papers are at NeurIPS 2026?

NeurIPS 2026 has 54 Physics-Informed ML papers, versus 65 the year before.

How many Physics-Informed ML papers are at ICLR 2026?

ICLR 2026 has 64 Physics-Informed ML papers, versus 38 the year before.

How many Physics-Informed ML papers are at ICML 2026?

ICML 2026 has 51 Physics-Informed ML papers, versus 25 the year before.

How many Physics-Informed ML papers are at CVPR 2026?

CVPR 2026 has 30 Physics-Informed ML papers, versus 19 the year before.

Which conference publishes the most Physics-Informed ML papers?

NeurIPS, with 167 papers from 2023 to 2026.