Bibhas Chakraborty

Statistics and Probability · 2008–2020

A researcher in the Science corpus: 8 papers; trusts 16 researchers and is trusted by 29 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 59 citations into it; #1,380 of 12,932 by trust here, #2,261 by citations
• Economics and Econometrics — 14 citations into it; #12,631 of 23,481 by trust here, #21,405 by citations
• Reinforcement Learning — 14 citations into it
• Causal Inference & Discovery — 6 citations into it
• Experimental and Cognitive Psychology — 6 citations into it; #4,561 of 9,731 by trust here, #7,727 by citations
• Statistical Learning Theory — 5 citations into it

Whom Bibhas Chakraborty trusts overall

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

1. Susan A. Murphy
2. James M. Robins
3. Richard S. Sutton
4. Robert Tibshirani
5. András Antos
6. Philip W. Lavori
7. Peter C. Austin
8. Andrew Barto
9. Jianwen Shao
10. Eric B. Laber

Who trusts Bibhas Chakraborty overall

1. Eric B. Laber
2. Kristin A. Linn
3. Chao Yu
4. Ying‐Qi Zhao
5. Jesse Clifton
6. Ying Liu
7. Daniel J. Lizotte
8. Abiral Baniya
9. Jiming Liu
10. Nathan Kallus

Papers from Bibhas Chakraborty's perspective

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

1. Regression Shrinkage and Selection via the Lasso
2. Reinforcement Learning: An Introduction
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. The Elements of Statistical Learning
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Long Short-Term Memory

Their papers

• Inference for Nonregular Parameters in Optimal Dynamic Treatment Regimes (2009) — 176 citations
• Statistical Methods for Dynamic Treatment Regimes: Reinforcement Learning, Causal Inference, and Personalized Medicine (2013) — 306 citations
• Inference for Optimal Dynamic Treatment Regimes Using an Adaptive m‐Out‐of‐n Bootstrap Scheme (2013) — 131 citations
• Statistical Reinforcement Learning (2013) — 20 citations
• Q-learning Residual Analysis: Application to The Effectiveness of Sequences of Antipsychotic Medications for Patients with Schizophrenia (2016) — 19 citations
• AutoScore: A Machine Learning–Based Automatic Clinical Score Generator and Its Application to Mortality Prediction Using Electronic Health Records (2020) — 123 citations
• Novel model for predicting inpatient mortality after emergency admission to hospital in Singapore: retrospective observational study (2019) — 21 citations
• Bias Correction and Confidence Intervals for Fitted Q-iteration (2008)