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Papers
Interpolating Neural Network-Tensor Decomposition (INN-TD): a scalable and interpretable approach for large-scale physics-based problems
ICML 2025
Learning a Neural Solver for Parametric PDEs to Enhance Physics-Informed Methods
ICLR 2025
Zebra: In-Context Generative Pretraining for Solving Parametric PDEs
ICML 2025
Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning
NeurIPS 2024
Optimal deep learning of holomorphic operators between Banach spaces
NeurIPS 2024
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks
ICML 2023
Multilevel CNNs for Parametric PDEs
JMLR 2023