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physics-informed machine learning

10 papers

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Also known as

PIML

Co-occurring keywords · papers mentioning both

partial differential equation (5) graph neural network (2) long-term prediction (2) irregular spaced data (1) temperature prediction (1) causal structure discovery (1) divergence-free flow (1) cardiac electrophysiology (1) neural oscillator (1) long-time dependency (1)

Papers

Bridging Machine Learning and Physics for Scalable Long-Term Building Temperature Prediction (Student Abstract) AAAI 2026 Causal Importance for Physics-Informed Machine Learning CLeaR 2026 Physically-Informed Flow Matching with Graph Neural Networks for Complex Fluid Dynamics AAAI 2026 Physics-Informed Neural Operators for Cardiac Electrophysiology L4DC 2026 A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems ICML 2025 Boundary constrained Gaussian processes for robust physics-informed machine learning of linear partial differential equations JMLR 2024 MetaPhysiCa: Improving OOD Robustness in Physics-informed Machine Learning ICLR 2024 Neural Oscillators for Generalization of Physics-Informed Machine Learning AAAI 2024 Physics-informed machine learning as a kernel method COLT 2024 SNN-PDE: Learning Dynamic PDEs from Data with Simplicial Neural Networks AAAI 2024