Learning in infinite dimension with neural operators.
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Updated
May 23, 2024 - Python
Learning in infinite dimension with neural operators.
DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia
Code for Characterizing Scaling and Transfer Learning Behavior of FNO in SciML
Implementation of Fourier Neural Operator from scratch
Code to reproduce the results in "Conditional score-based diffusion models for Bayesian inference in infinite dimensions", NeurIPS 2023
The first GAN-based tabular data synthesizer integrating the Fourier Neural Operator for global dependency imitation
An extension of Fourier Neural Operator to finite-dimensional input and/or output spaces.
Code for the paper "The Random Feature Model for Input-Output Maps between Banach Spaces"
Code for the paper ``Error Bounds for Learning with Vector-Valued Random Features''
Neural Operator-Assisted Computational Fluid Dynamics in PyTorch
Solving multiphysics-based inverse problems with learned surrogates and constraints
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