Collection of popular and reproducible image denoising works.
-
Updated
Dec 5, 2021
Collection of popular and reproducible image denoising works.
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
[NeurIPS 2022] Denoising Diffusion Restoration Models -- Official Code Repository
Official implementation of Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restoration
[ECCV 2024] InstructIR: High-Quality Image Restoration Following Human Instructions https://huggingface.co/spaces/marcosv/InstructIR
Simulation and Parameter Estimation in Geophysics - A python package for simulation and gradient based parameter estimation in the context of geophysical applications.
Physics Informed Machine Learning Tutorials (Pytorch and Jax)
Official pytorch repository for "Diffusion Posterior Sampling for General Noisy Inverse Problems"
PyLops – A Linear-Operator Library for Python
AI Image SIgnal Processing and Computational Photography - Bokeh Rendering , Reversed ISP Challenge, Model-Based Image Signal Processors via Learnable Dictionaries. Official repo for NTIRE and AIM Challenges
Operator Discretization Library https://odlgroup.github.io/odl/
Code repository for our paper DiffCloth: Differentiable Cloth Simulation with Dry Frictional Contact
PyTorch library for solving imaging inverse problems using deep learning
🦐 Electromagnetic Simulation + Automatic Differentiation
PDE-Net: Learning PDEs from Data
Rectified Flow Inversion (RF-Inversion)
Deep learning framework for MRI reconstruction
Probabilistic Inference on Noisy Time Series
Forward modeling, inversion, and processing gravity and magnetic data
Add a description, image, and links to the inverse-problems topic page so that developers can more easily learn about it.
To associate your repository with the inverse-problems topic, visit your repo's landing page and select "manage topics."