A Python convex optimization package using proximal splitting methods
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Updated
Aug 18, 2023 - Python
A Python convex optimization package using proximal splitting methods
Scientific Computational Imaging COde
Implementation of "Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems"
Python routines to compute the Total Variation (TV) of 2D, 3D and 4D images on CPU & GPU. Compatible with proximal algorithms (ADMM, Chambolle & Pock, ...)
New Matrix Factorization Algorithms based on Bregman Proximal Gradient: BPG-MF, CoCaIn BPG-MF, BPG-MF-WB
Primal-Dual Solver for Inverse Problems
A Python package which implements the Elastic Net using the (accelerated) proximal gradient method.
CoCaIn BPG escapes Spurious Stationary Points
An efficient GPU-compatible library built on PyTorch, offering a wide range of proximal operators and constraints for optimization and machine learning tasks.
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