Matlab/Python codes
Code of some selected works.
S. Mukherjee et al., "End-to-end reconstruction meets data-driven regularization for inverse problems," arXiv:2106.03538v1.
S. Mukherjee et al., "Adversarially learned iterative reconstruction for imaging inverse problems," arXiv:2103.16151v1, Mar. 2021.
S. Mukherjee et al., "Learned convex regularizers for inverse problems," arXiv:2008.02839v2, Mar. 2021.
"Phase retrieval from binary measurements," IEEE Signal Process. Lett., vol. 25, no. 3, pp. 348–352, Mar. 2018.
"DNNs for sparse coding and dictionary learning," Bayesian Deep Learning Workshop, Neural Info. Process. Systems (NIPS), Dec. 2017. (Python code developed by D. Mahapatra)
"L1-K-SVD: A robust dictionary learning algorithm with simultaneous update," Signal Process. (Elsevier), vol. 123, pp. 42–52, Jun. 2016.
"Fienup algorithm with sparsity constraints: Application to frequency-domain optical-coherence tomography," IEEE Trans. Signal Process., vol. 62, no. 18, pp. 4659–4672, Sep. 2014.