This page provides information about open source software in which I have contributed significantly.
CR-Sparse is a Python library that enables efficiently solving a wide variety of sparse representation based signal processing problems. It is a cohesive collection of sub-libraries working together. Individual sub-libraries provide functionalities for: wavelets, linear operators, greedy and convex optimization based sparse recovery algorithms, subspace clustering, standard signal processing transforms, and linear algebra subroutines for solving sparse linear systems. It has been built using Google JAX, which enables the same high level Python code to get efficiently compiled on CPU, GPU and TPU architectures using XLA.
A MATLAB library for exploiting the sparsity in data representations for solving real life problems.