Matteo Sesia

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 21 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it; #12,934 of 35,345 by trust here, #23,731 by citations
• Statistics and Probability — 12 citations into it; #4,603 of 12,932 by trust here, #6,552 by citations
• Evaluation & Benchmarks — 6 citations into it

Whom Matteo Sesia trusts overall

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

1. Harris Papadopoulos
2. Nicolai Meinshausen
3. Vladimir G Vovk
4. James W. Taylor
5. Jing Lei
6. Yaniv Romano
7. Roger W. Koenker
8. A. Gammerman
9. E.J. Candes
10. Robert Tibshirani

Who trusts Matteo Sesia overall

1. Maxime Cauchois
2. Yaniv Romano
3. Suyash Gupta
4. E.J. Candes
5. Anastasios Nikolas Angelopoulos
6. Leying Guan
7. John C. Duchi
8. Lihua Lei
9. Stephen Bates

Papers from Matteo Sesia's perspective

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

1. Algorithmic Learning in a Random World
2. ImageNet classification with deep convolutional neural networks
3. Regression Shrinkage and Selection via the Lasso
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Inductive Confidence Machines for Regression
6. Distribution‐free prediction bands for non‐parametric regression
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. Gradient-based learning applied to document recognition
9. Machine-Learning Applications of Algorithmic Randomness
10. Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likelihood Methods

Their papers

• Classification with Valid and Adaptive Coverage (2020) — 528 citations
• A comparison of some conformal quantile regression methods (2019) — 140 citations