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

21 papers, page 1 of 1

1. NeurIPS 2023ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation
2. NeurIPS 2023Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs
3. NeurIPS 2023Gradient Informed Proximal Policy Optimization
4. NeurIPS 2023H-InDex: Visual Reinforcement Learning with Hand-Informed Representations for Dexterous Manipulation
5. NeurIPS 2023High-dimensional Asymptotics of Denoising Autoencoders
6. NeurIPS 2023Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks
7. NeurIPS 2023Inferring Hybrid Neural Fluid Fields from Videos
8. NeurIPS 2023InsActor: Instruction-driven Physics-based Characters
9. NeurIPS 2023Lie Point Symmetry and Physics-Informed Networks
10. NeurIPS 2023Nonparametric Boundary Geometry in Physics Informed Deep Learning
11. NeurIPS 2023Physics-Driven ML-Based Modelling for Correcting Inverse Estimation
12. NeurIPS 2023Physics-Informed Bayesian Optimization of Variational Quantum Circuits
13. NeurIPS 2023PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification
14. NeurIPS 2023Proximity-Informed Calibration for Deep Neural Networks
15. NeurIPS 2023ResoNet: Noise-Trained Physics-Informed MRI Off-Resonance Correction
16. NeurIPS 2023Separable Physics-Informed Neural Networks
17. NeurIPS 2023Solving Inverse Physics Problems with Score Matching
18. NeurIPS 2023Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints
19. NeurIPS 2023Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials
20. NeurIPS 2023SyncTREE: Fast Timing Analysis for Integrated Circuit Design through a Physics-informed Tree-based Graph Neural Network
21. NeurIPS 2023Versatile Energy-Based Probabilistic Models for High Energy Physics

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.