Esteban G. Tabak

Statistics and Probability · 2010–2018

A researcher in the Science corpus: 4 papers; trusts 40 researchers and is trusted by 57 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 21 citations into it; #1,120 of 12,932 by trust here, #1,860 by citations
• Artificial Intelligence — 19 citations into it; #4,989 of 35,345 by trust here, #14,181 by citations
• Computer Vision and Pattern Recognition — 16 citations into it; #11,282 of 21,575 by trust here, #20,271 by citations
• Statistical Learning Theory — 12 citations into it; #706 of 1,038 by trust here, #985 by citations
• Probabilistic & Bayesian Methods — 8 citations into it; #287 of 1,525 by trust here, #451 by citations
• Applied Mathematics — 7 citations into it
• Signal Processing — 6 citations into it; #3,652 of 7,572 by trust here, #6,836 by citations
• Statistical and Nonlinear Physics — 5 citations into it

Whom Esteban G. Tabak trusts overall

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

1. David X. Li
2. Radford M. Neal
3. Jean-David Benamou
4. Christopher K. I. Williams
5. Huaiyu Zhu
6. Marco Cuturi
7. R. Fisher
8. Eric R. Ziegel
9. Christian Bauckhage
10. Barnab'as P'oczos

Who trusts Esteban G. Tabak overall

1. Michael S. Albergo
2. Laurent Dinh
3. J. Tomczak
4. Danilo Jimenez Rezende
5. Hao Wu
6. Rui Huang
7. Eric T. Nalisnick
8. Eric Vanden-Eijnden
9. Max Welling
10. Jonas Köhler

Papers from Esteban G. Tabak's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Learning Multiple Layers of Features from Tiny Images
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. GENERATIVE ADVERSARIAL NETS
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A Family of Nonparametric Density Estimation Algorithms (2013) — 553 citations
• DENSITY ESTIMATION BY DUAL ASCENT OF THE LOG-LIKELIHOOD ∗ (2010) — 432 citations
• Explanation of Variability and Removal of Confounding Factors from Data through Optimal Transport (2018) — 26 citations
• Prototypal Analysis and Prototypal Regression (2017) — 13 citations