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

27 papers, page 1 of 1

1. NeurIPS 2024A Phase Transition between Positional and Semantic Learning in a Solvable Model of Dot-Product Attention
2. NeurIPS 2024ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction
3. NeurIPS 2024Constrained Synthesis with Projected Diffusion Models
4. NeurIPS 2024CryoGEM: Physics-Informed Generative Cryo-Electron Microscopy
5. NeurIPS 2024DEL: Discrete Element Learner for Learning 3D Particle Dynamics with Neural Rendering
6. NeurIPS 2024Dual Cone Gradient Descent for Training Physics-Informed Neural Networks
7. NeurIPS 2024How does PDE order affect the convergence of PINNs?
8. NeurIPS 2024Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks
9. NeurIPS 2024Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics
10. NeurIPS 2024Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods
11. NeurIPS 2024Med-Real2Sim: Non-Invasive Medical Digital Twins using Physics-Informed Self-Supervised Learning
12. NeurIPS 2024Meta-Learning Universal Priors Using Non-Injective Change of Variables
13. NeurIPS 2024Multi-Object 3D Grounding with Dynamic Modules and Language-Informed Spatial Attention
14. NeurIPS 2024Multiple Physics Pretraining for Spatiotemporal Surrogate Models
15. NeurIPS 2024Newton Informed Neural Operator for Solving Nonlinear Partial Differential Equations
16. NeurIPS 2024P$^2$C$^2$Net: PDE-Preserved Coarse Correction Network for efficient prediction of spatiotemporal dynamics
17. NeurIPS 2024Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guarantees
18. NeurIPS 2024Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling
19. NeurIPS 2024Physics-Informed Variational State-Space Gaussian Processes
20. NeurIPS 2024Physics-Regularized Multi-Modal Image Assimilation for Brain Tumor Localization
21. NeurIPS 2024PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs
22. NeurIPS 2024Posture-Informed Muscular Force Learning for Robust Hand Pressure Estimation
23. NeurIPS 2024RoPINN: Region Optimized Physics-Informed Neural Networks
24. NeurIPS 2024SEA: State-Exchange Attention for High-Fidelity Physics Based Transformers
25. NeurIPS 2024The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks
26. NeurIPS 2024Transfer Learning with Informative Priors: Simple Baselines Better than Previously Reported
27. NeurIPS 2024What is my quantum computer good for? Quantum capability learning with physics-aware neural networks

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.