Mohsen Bayati

Statistics and Probability · 2010–2020

A researcher in the Science corpus: 6 papers; trusts 40 researchers and is trusted by 46 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 48 citations into it; #9,519 of 12,932 by trust here, #5,294 by citations
• Artificial Intelligence — 43 citations into it; #10,438 of 35,345 by trust here, #25,040 by citations
• Management Science and Operations Research — 34 citations into it; #2,612 of 11,946 by trust here, #6,888 by citations
• Computational Mechanics — 28 citations into it; #516 of 10,001 by trust here, #2,032 by citations
• Computer Networks and Communications — 21 citations into it; #669 of 9,886 by trust here, #2,927 by citations
• Statistical Learning Theory — 17 citations into it
• Reinforcement Learning — 15 citations into it
• Optimization & Training — 14 citations into it

Whom Mohsen Bayati trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. David L. Donoho
2. Robert Tibshirani
3. Andrea Montanari
4. E.J. Candes
5. Alexandre B. Tsybakov
6. Arian Maleki
7. T. Richardson
8. Peter Auer
9. Eric R. Ziegel
10. Aleksandrs Slivkins

Who trusts Mohsen Bayati overall

1. Greg Yang
2. E.J. Candes
3. Sundeep Rangan
4. Susan Athey
5. Pragya Sur
6. Junjie Ma
7. Andrea Montanari
8. Noureddine El Karoui
9. David L. Donoho
10. Jean Barbier

Papers from Mohsen Bayati's perspective

Ordered by how strongly the researchers Mohsen Bayati trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Regression Shrinkage and Selection via the Lasso
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. The Elements of Statistical Learning
8. Atomic Decomposition by Basis Pursuit
9. Long Short-Term Memory
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• NBER WORKING PAPER SERIES MATRIX COMPLETION METHODS FOR CAUSAL PANEL DATA MODELS (2018)
• Ensemble Methods for Causal Effects in Panel Data Settings (2019) — 48 citations
• Online Decision Making with High-Dimensional Covariates (2020) — 433 citations
• Exploiting the Natural Exploration In Contextual Bandits (2017) — 30 citations
• The LASSO Risk for Gaussian Matrices (2010) — 333 citations
• The dynamics of message passing on dense graphs, with applications to compressed sensing (2010) — 1,095 citations