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Subhadip Mukherjee
Subhadip Mukherjee
Assistant Professor, Department of E&ECE, IIT Kharagpur, India
Verified email at ece.iitkgp.ac.in - Homepage
Title
Cited by
Cited by
Year
An iterative algorithm for phase retrieval with sparsity constraints: application to frequency domain optical coherence tomography
S Mukherjee, CS Seelamantula
2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012
762012
Learned convex regularizers for inverse problems
S Mukherjee, S Dittmer, Z Shumaylov, S Lunz, O Öktem, CB Schönlieb
arxiv preprint (arXiv:2008.02839v1), 2020
712020
Learned reconstruction methods with convergence guarantees: A survey of concepts and applications
S Mukherjee, A Hauptmann, O Öktem, M Pereyra, CB Schönlieb
IEEE Signal Processing Magazine 40 (1), 164-182, 2023
672023
Fienup algorithm with sparsity constraints: Application to frequency-domain optical-coherence tomography
S Mukherjee, CS Seelamantula
Signal Processing, IEEE Transactions on 62 (18), 4659-4672, 2014
542014
End-to-end reconstruction meets data-driven regularization for inverse problems
S Mukherjee, M Carioni, O Öktem, CB Schönlieb
Thirty-Fifth Conference on Neural Information Processing Systems, 2021
452021
ℓ1-K-SVD: A robust dictionary learning algorithm with simultaneous update
S Mukherjee, R Basu, CS Seelamantula
Signal Processing 123, 42-52, 2016
452016
Learning convex regularizers satisfying the variational source condition for inverse problems
S Mukherjee, CB Schönlieb, M Burger
NeurIPS-2021 Workshop on Deep Learning and Inverse Problems, 2021
282021
An optimum shrinkage estimator based on minimum-probability-of-error criterion and application to signal denoising
J Sadasivan, S Mukherjee, CS Seelamantula
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International …, 2014
252014
Joint dictionary training for bandwidth extension of speech signals
J Sadasivan, S Mukherjee, CS Seelamantula
2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016
242016
Data-driven mirror descent with input-convex neural networks
HY Tan, S Mukherjee, J Tang, CB Schönlieb
accepted to the SIAM Journal on Mathematics of Data Science (SIMODS), 2022
172022
Deep sparse coding using optimized linear expansion of thresholds
D Mahapatra, S Mukherjee, CS Seelamantula
arXiv preprint arXiv:1705.07290, 2017
172017
Provably convergent plug-and-play quasi-Newton methods
HY Tan, S Mukherjee, J Tang, CB Schönlieb
SIAM Journal on Imaging Sciences 17 (2), 785-819, 2024
142024
Deep learning-based Segmentation of Multi-site Disease in Ovarian Cancer
T Buddenkotte, L Rundo, R Woitek, L Escudero Sanchez, L Beer, ...
medRxiv, 2023
142023
Convergent regularization in inverse problems and linear plug-and-play denoisers
A Hauptmann, S Mukherjee, CB Schönlieb, F Sherry
arXiv:2307.09441, 2023
122023
Phase retrieval from binary measurements
S Mukherjee, CS Seelamantula
IEEE Signal Processing Letters 25 (3), 348-352, 2018
102018
Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI
S Saitta, M Carioni, S Mukherjee, CB Schönlieb, A Redaelli
Computer Methods and Programs in Biomedicine 246, 108057, 2024
92024
Stochastic primal-dual deep unrolling
J Tang, S Mukherjee, CB Schönlieb
arXiv preprint arXiv:2110.10093, 2021
92021
Data-Driven Convex Regularizers for Inverse Problems
S Mukherjee, S Dittmer, Z Shumaylov, S Lunz, O Öktem, CB Schönlieb
ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024
82024
NF-ULA: Langevin Monte Carlo with normalizing flow prior for imaging inverse problems
Z Cai, J Tang, S Mukherjee, J Li, CB Schönlieb, X Zhang
arXiv preprint arXiv:2304.08342, 2023
82023
Tree species classification from hyperspectral data using graph-regularized neural networks
D Bandyopadhyay, S Mukherjee, J Ball, G Vincent, DA Coomes, ...
arXiv preprint arXiv:2208.08675, 2022
82022
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Articles 1–20