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

481 papers, page 5 of 10

201. CVPR 2025DexGrasp Anything: Towards Universal Robotic Dexterous Grasping with Physics Awareness
202. CVPR 2025Electromyography-Informed Facial Expression Reconstruction for Physiological-Based Synthesis and Analysis
203. CVPR 2025FiRe: Fixed-points of Restoration Priors for Solving Inverse Problems
204. CVPR 2025FLAIR: VLM with Fine-grained Language-informed Image Representations
205. CVPR 2025FreeGave: 3D Physics Learning from Dynamic Videos by Gaussian Velocity
206. CVPR 2025Learning Physics-Based Full-Body Human Reaching and Grasping from Brief Walking References
207. CVPR 2025Nested Diffusion Models Using Hierarchical Latent Priors
208. CVPR 2025Patient-Level Anatomy Meets Scanning-Level Physics: Personalized Federated Low-Dose CT Denoising Empowered by Large Language Model
209. CVPR 2025PBR-NeRF: Inverse Rendering with Physics-Based Neural Fields
210. CVPR 2025Point Clouds Meets Physics: Dynamic Acoustic Field Fitting Network for Point Cloud Understanding
211. CVPR 2025POMP: Physics-consistent Motion Generative Model through Phase Manifolds
212. CVPR 2025Pose Priors from Language Models
213. CVPR 2025Relative Pose Estimation through Affine Corrections of Monocular Depth Priors
214. CVPR 2025S^3-Face: SSS-Compliant Facial Reflectance Estimation via Diffusion Priors
215. CVPR 2025SpatialLLM: A Compound 3D-Informed Design towards Spatially-Intelligent Large Multimodal Models
216. CVPR 2025Spectral Informed Mamba for Robust Point Cloud Processing
217. CVPR 2025UniPhy: Learning a Unified Constitutive Model for Inverse Physics Simulation
218. CVPR 2025VI^3NR: Variance Informed Initialization for Implicit Neural Representations
219. ICLR 2025ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning
220. ICLR 2025Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences
221. ICLR 2025Beyond the convexity assumption: Realistic tabular data generation under quantifier-free real linear constraints
222. ICLR 2025Circuit Transformer: A Transformer That Preserves Logical Equivalence
223. ICLR 2025ConFIG: Towards Conflict-free Training of Physics Informed Neural Networks
224. ICLR 2025Deep Learning Alternatives Of The Kolmogorov Superposition Theorem
225. ICLR 2025Differentiable Rule Induction from Raw Sequence Inputs
226. ICLR 2025Dream to Manipulate: Compositional World Models Empowering Robot Imitation Learning with Imagination
227. ICLR 2025Generating Physical Dynamics under Priors
228. ICLR 2025KLay: Accelerating Arithmetic Circuits for Neurosymbolic AI
229. ICLR 2025Learning a Neural Solver for Parametric PDEs to Enhance Physics-Informed Methods
230. ICLR 2025Learning Chaos In A Linear Way
231. ICLR 2025Learning system dynamics without forgetting
232. ICLR 2025Learning to Solve Differential Equation Constrained Optimization Problems
233. ICLR 2025Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups
234. ICLR 2025Logically Consistent Language Models via Neuro-Symbolic Integration
235. ICLR 2025MeshMask: Physics-Based Simulations with Masked Graph Neural Networks
236. ICLR 2025Metamizer: A Versatile Neural Optimizer for Fast and Accurate Physics Simulations
237. ICLR 2025NeSyC: A Neuro-symbolic Continual Learner For Complex Embodied Tasks In Open Domains
238. ICLR 2025Neural Stochastic Differential Equations for Uncertainty-Aware Offline RL
239. ICLR 2025Neural Wave Equation for Irregularly Sampled Sequence Data
240. ICLR 2025Physics of Language Models: Part 2.2, How to Learn From Mistakes on Grade-School Math Problems
241. ICLR 2025Physics-aligned field reconstruction with diffusion bridge
242. ICLR 2025Physics-Informed Diffusion Models
243. ICLR 2025Physics-informed Temporal Difference Metric Learning for Robot Motion Planning
244. ICLR 2025PIED: Physics-Informed Experimental Design for Inverse Problems
245. ICLR 2025PIG: Physics-Informed Gaussians as Adaptive Parametric Mesh Representations
246. ICLR 2025PINP: Physics-Informed Neural Predictor with latent estimation of fluid flows
247. ICLR 2025PIORF: Physics-Informed Ollivier-Ricci Flow for Long–Range Interactions in Mesh Graph Neural Networks
248. ICLR 2025PRDP: Progressively Refined Differentiable Physics
249. ICLR 2025Predicting the Energy Landscape of Stochastic Dynamical System via Physics-informed Self-supervised Learning
250. ICLR 2025Rethinking the role of frames for SE(3)-invariant crystal structure modeling

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.