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

143 papers, page 3 of 3

101. ICLR 2025Symbolic regression via MDLformer-guided search: from minimizing prediction error to minimizing description length
102. ICLR 2025Towards Automated Knowledge Integration From Human-Interpretable Representations
103. ICLR 2024AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction
104. ICLR 2024An operator preconditioning perspective on training in physics-informed machine learning
105. ICLR 2024CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing
106. ICLR 2024Crystalformer: Infinitely Connected Attention for Periodic Structure Encoding
107. ICLR 2024DATS: Difficulty-Aware Task Sampler for Meta-Learning Physics-Informed Neural Networks
108. ICLR 2024Dynamics-Informed Protein Design with Structure Conditioning
109. ICLR 2024Generating Pragmatic Examples to Train Neural Program Synthesizers
110. ICLR 2024Guess & Sketch: Language Model Guided Transpilation
111. ICLR 2024How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data
112. ICLR 2024Incremental Randomized Smoothing Certification
113. ICLR 2024Interpreting Robustness Proofs of Deep Neural Networks
114. ICLR 2024Lagrangian Flow Networks for Conservation Laws
115. ICLR 2024Latent Intuitive Physics: Learning to Transfer Hidden Physics from A 3D Video
116. ICLR 2024Learning Grounded Action Abstractions from Language
117. ICLR 2024LEGO-Prover: Neural Theorem Proving with Growing Libraries
118. ICLR 2024Lemur: Integrating Large Language Models in Automated Program Verification
119. ICLR 2024Let's do the time-warp-attend: Learning topological invariants of dynamical systems
120. ICLR 2024LILO: Learning Interpretable Libraries by Compressing and Documenting Code
121. ICLR 2024Logical Languages Accepted by Transformer Encoders with Hard Attention
122. ICLR 2024Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation
123. ICLR 2024Long-Term Typhoon Trajectory Prediction: A Physics-Conditioned Approach Without Reanalysis Data
124. ICLR 2024MetaPhysiCa: Improving OOD Robustness in Physics-informed Machine Learning
125. ICLR 2024Neural-Symbolic Recursive Machine for Systematic Generalization
126. ICLR 2024NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks
127. ICLR 2024Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings
128. ICLR 2024PINNACLE: PINN Adaptive ColLocation and Experimental points selection
129. ICLR 2024PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks
130. ICLR 2024Reclaiming the Source of Programmatic Policies: Programmatic versus Latent Spaces
131. ICLR 2024Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors
132. ICLR 2024Scaling physics-informed hard constraints with mixture-of-experts
133. ICLR 2024Sliced Denoising: A Physics-Informed Molecular Pre-Training Method
134. ICLR 2024Stabilizing Backpropagation Through Time to Learn Complex Physics
135. ICLR 2023Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients
136. ICLR 2023Competitive Physics Informed Networks
137. ICLR 2023DiffMimic: Efficient Motion Mimicking with Differentiable Physics
138. ICLR 2023Guiding continuous operator learning through Physics-based boundary constraints
139. ICLR 2023Improved Training of Physics-Informed Neural Networks Using Energy-Based Priors: a Study on Electrical Impedance Tomography
140. ICLR 2023NTFields: Neural Time Fields for Physics-Informed Robot Motion Planning
141. ICLR 2023Phase2vec: dynamical systems embedding with a physics-informed convolutional network
142. ICLR 2023Simple initialization and parametrization of sinusoidal networks via their kernel bandwidth
143. ICLR 2023Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation

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.