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Code for Lensless Learning Paper
A matlab code for "inverse problems" based image reconstruction of digital in-line holograms.
Algorithms for pixel super-resolution phase retrieval
[ECCV 2024] Test-time Model Adaptation for Image Reconstruction Using Self-supervised Adaptive Layers
Deep learning for holographic imaging with random illuminations. Uses autoencoders for twin image removal and blind single-shot reconstruction without needing ground truth.
DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia
Physics-informed Deep Compositional Operator Network
DeepONet & FNO (with practical extensions)
This repository is the official project page of the course AI in the Sciences and Engineering, ETH Zurich.
Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."
Pytorch implementation for Error Reduction algorithm and Hybrid input-output algorithm.
ICML2024: Equivariant Graph Neural Operator for Modeling 3D Dynamics
U-FNO - an enhanced Fourier neural operator-based deep-learning model for multiphase flow
A library for Koopman Neural Operator with Pytorch.
Python Reconstruction Operators in Neural Networks. High level python API for PYRO-NN-Layers
Learning in infinite dimension with neural operators.
Diffraction Deep Neural Networks(D2NN)
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
《笨方法学 Python》（Learn Python the Hard Way）学习笔记