Vector approximate message passing S Rangan, P Schniter, AK Fletcher Information Theory (ISIT), 2017 IEEE International Symposium on, 1588-1592, 2017 | 572 | 2017 |
Compressive sampling and lossy compression VK Goyal, AK Fletcher, S Rangan IEEE Signal Processing Magazine 25 (2), 48-56, 2008 | 326 | 2008 |
On the convergence of approximate message passing with arbitrary matrices S Rangan, P Schniter, AK Fletcher, S Sarkar IEEE Transactions on Information Theory 65 (9), 5339-5351, 2019 | 293 | 2019 |
Necessary and sufficient conditions for sparsity pattern recovery AK Fletcher, S Rangan, VK Goyal IEEE Transactions on Information Theory 55 (12), 5758-5772, 2009 | 274 | 2009 |
Asymptotic analysis of map estimation via the replica method and compressed sensing S Rangan, V Goyal, AK Fletcher Advances in Neural Information Processing Systems 22, 2009 | 254 | 2009 |
Vector approximate message passing for the generalized linear model P Schniter, S Rangan, AK Fletcher 2016 50th Asilomar conference on signals, systems and computers, 1525-1529, 2016 | 150 | 2016 |
Distributed source coding: theory, algorithms and applications PL Dragotti, M Gastpar Academic Press, 2009 | 145 | 2009 |
Robust predictive quantization: Analysis and design via convex optimization AK Fletcher, S Rangan, VK Goyal, K Ramchandran Selected Topics in Signal Processing, IEEE Journal of 1 (4), 618-632, 2007 | 127 | 2007 |
Iterative reconstruction of rank-one matrices in noise AK Fletcher, S Rangan Information and Inference: A Journal of the IMA, 2018 | 124* | 2018 |
Fixed points of generalized approximate message passing with arbitrary matrices S Rangan, P Schniter, E Riegler, AK Fletcher, V Cevher IEEE Transactions on Information Theory 62 (12), 7464-7474, 2016 | 113 | 2016 |
Estimation from lossy sensor data: Jump linear modeling and Kalman filtering AK Fletcher, S Rangan, VK Goyal Proceedings of the 3rd international symposium on Information processing in …, 2004 | 102 | 2004 |
Approximate Message Passing With Consistent Parameter Estimation and Applications to Sparse Learning U Kamilov, S Rangan, AK Fletcher, M Unser IEEE Transactions on Information Theory 60 (5), 2969-2985, 2014 | 99 | 2014 |
On-off random access channels: A compressed sensing framework AK Fletcher, S Rangan, VK Goyal arXiv preprint arXiv:0903.1022, 2009 | 87 | 2009 |
Expectation consistent approximate inference: Generalizations and convergence A Fletcher, M Sahraee-Ardakan, S Rangan, P Schniter 2016 IEEE International Symposium on Information Theory (ISIT), 190-194, 2016 | 79 | 2016 |
Inference in deep networks in high dimensions AK Fletcher, S Rangan, P Schniter 2018 IEEE International Symposium on Information Theory (ISIT), 1884-1888, 2018 | 75 | 2018 |
On the rate-distortion performance of compressed sensing AK Fletcher, S Rangan, VK Goyal 2007 IEEE International Conference on Acoustics, Speech and Signal …, 2007 | 75 | 2007 |
Inference for generalized linear models via alternating directions and Bethe free energy minimization S Rangan, AK Fletcher, P Schniter, US Kamilov IEEE Transactions on Information Theory 63 (1), 676-697, 2016 | 74 | 2016 |
Denoising by sparse approximation: Error bounds based on rate-distortion theory AK Fletcher, S Rangan, VK Goyal, K Ramchandran EURASIP Journal on Advances in Signal Processing 2006, 1-19, 2006 | 72 | 2006 |
Plug-in estimation in high-dimensional linear inverse problems: A rigorous analysis AK Fletcher, P Pandit, S Rangan, S Sarkar, P Schniter Advances in Neural Information Processing Systems 31, 2018 | 71 | 2018 |
Wavelet denoising by recursive cycle spinning AK Fletcher, K Ramchandran, VK Goyal Proceedings. International Conference on Image Processing 2, II-II, 2002 | 69 | 2002 |