Ethan Caballero

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 3 papers; trusts 64 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 92 citations into it
• Computer Vision and Pattern Recognition — 59 citations into it
• Statistics and Probability — 11 citations into it
• Evaluation & Benchmarks — 9 citations into it
• Causal Inference & Discovery — 8 citations into it
• Optimization & Training — 7 citations into it
• Model Architectures — 5 citations into it

Whom Ethan Caballero trusts overall

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

1. Geoffrey E. Hinton
2. Jan Peters
3. Alex Krizhevsky
4. Kaiming He
5. Yoshua Bengio
6. Diederik P. Kingma
7. Yann LeCun
8. Vladimir Naumovich Vapnik
9. Karen Simonyan
10. Radford M. Neal

Who trusts Ethan Caballero overall

1. Elan Rosenfeld
2. Polina Kirichenko
3. Elliot Creager
4. Siqi Miao

Papers from Ethan Caballero's perspective

Ordered by how strongly the researchers Ethan Caballero 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. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Out-of-Distribution Generalization via Risk Extrapolation (REx) (2020) — 1,228 citations
• Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization (2021) — 353 citations
• Scaling Laws for the Few-Shot Adaptation of Pre-trained Image Classifiers (2021) — 12 citations