Isaac Gibbs

Artificial Intelligence · 2021–2023

A researcher in the Science corpus: 2 papers; trusts 16 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it; #32,425 of 35,345 by trust here, #33,294 by citations
• Statistics and Probability — 18 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Isaac Gibbs trusts overall

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

1. Vladimir G Vovk
2. Harris Papadopoulos
3. Rina Foygel Barber
4. E.J. Candes
5. Robert Tibshirani
6. Yaniv Romano
7. Jing Lei
8. Glenn Shafer
9. Tim Bollerslev
10. Shahar Mendelson

Who trusts Isaac Gibbs overall

1. Anastasios Nikolas Angelopoulos
2. Stephen Bates

Papers from Isaac Gibbs's perspective

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

1. Algorithmic Learning in a Random World
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Regression Shrinkage and Selection via the Lasso
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet classification with deep convolutional neural networks
6. Inductive Confidence Machines for Regression
7. Distribution‐free prediction bands for non‐parametric regression
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. Dropout: a simple way to prevent neural networks from overfitting

Their papers

• Adaptive Conformal Inference Under Distribution Shift (2021) — 508 citations
• Conformal prediction with conditional guarantees (2023) — 166 citations