Learning in infinite dimension with neural operators.
PDEBench: An Extensive Benchmark for Scientific Machine Learning
Physics-Informed Neural networks for Advanced modeling
This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs
A Library for Advanced Neural PDE Solvers.
Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."
Learning function operators with neural networks.
[ICLR24] A boundary-embedded neural operator that incorporates complex boundary shape and inhomogeneous boundary values
Rheology-informed Machine Learning Projects
Bridging Neural Operators and Numerical Methods
Official implementation of Operator-ProbConserv: OOD UQ for Neural Operators
Implementation of Fourier Neural Operator from scratch
[ICPR 2024] FNOReg: Resolution-Robust Medical Image Registration Method Based on Fourier Neural Operator
Final projects for 401-4656-21L AI in Sciences and Engineering @ ETHz. Includes implementation of Fourier Neural Operator (FNO) with time dependency, data-driven symbolic regression with PDE-Find and foundation model based on FNO for phase-field dynamics
Physics-Enhanced Machine Learning
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