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

25 papers, page 1 of 1

1. ICML 2025A Machine Learning Approach to Duality in Statistical Physics
2. ICML 2025Calibrated Physics-Informed Uncertainty Quantification
3. ICML 2025Causal-PIK: Causality-based Physical Reasoning with a Physics-Informed Kernel
4. ICML 2025Context-Informed Neural ODEs Unexpectedly Identify Broken Symmetries: Insights from the Poincaré–Hopf Theorem
5. ICML 2025CoPINN: Cognitive Physics-Informed Neural Networks
6. ICML 2025DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction
7. ICML 2025Evolving Minds: Logic-Informed Inference from Temporal Action Patterns
8. ICML 2025Geometry-Informed Neural Networks
9. ICML 2025Holistic Physics Solver: Learning PDEs in a Unified Spectral-Physical Space
10. ICML 2025Learning Single Index Models with Diffusion Priors
11. ICML 2025MIPT: Multilevel Informed Prompt Tuning for Robust Molecular Property Prediction
12. ICML 2025MultiPDENet: PDE-embedded Learning with Multi-time-stepping for Accelerated Flow Simulation
13. ICML 2025Near-optimal Sketchy Natural Gradients for Physics-Informed Neural Networks
14. ICML 2025NEAR: Neural Electromagnetic Array Response
15. ICML 2025PEINR: A Physics-enhanced Implicit Neural Representation for High-Fidelity Flow Field Reconstruction
16. ICML 2025Physics-Informed DeepONets for drift-diffusion on metric graphs: simulation and parameter identification
17. ICML 2025Physics-Informed Generative Modeling of Wireless Channels
18. ICML 2025Physics-informed Temporal Alignment for Auto-regressive PDE Foundation Models
19. ICML 2025Physics-Informed Weakly Supervised Learning For Interatomic Potentials
20. ICML 2025PINNsAgent: Automated PDE Surrogation with Large Language Models
21. ICML 2025Refined generalization analysis of the Deep Ritz Method and Physics-Informed Neural Networks
22. ICML 2025Riemann Tensor Neural Networks: Learning Conservative Systems with Physics-Constrained Networks
23. ICML 2025Structure-informed Risk Minimization for Robust Ensemble Learning
24. ICML 2025Sub-Sequential Physics-Informed Learning with State Space Model
25. ICML 2025Topology-aware Neural Flux Prediction Guided by 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.