Ethan R. Elenberg

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 3 papers; trusts 101 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 65 citations into it; #13,310 of 35,345 by trust here, #15,866 by citations
• Optimization & Training — 31 citations into it; #1,799 of 2,601 by trust here, #2,052 by citations
• Computer Vision and Pattern Recognition — 29 citations into it
• Computational Theory and Mathematics — 13 citations into it; #7,227 of 12,182 by trust here, #6,463 by citations
• Computational Mechanics — 11 citations into it; #5,857 of 10,001 by trust here, #6,041 by citations
• Representation & Self-Supervised Learning — 6 citations into it
• Statistics and Probability — 6 citations into it

Whom Ethan R. Elenberg trusts overall

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

1. Tong Zhang
2. George L. Nemhauser
3. Francis R. Bach
4. Alex Krizhevsky
5. Christian Szegedy
6. Geoffrey E. Hinton
7. Lawrence D. Brown
8. Yoshua Bengio
9. Kaiming He
10. Joel A. Tropp

Who trusts Ethan R. Elenberg overall

1. Sharon Qian
2. Karthik S. Gurumoorthy
3. Christopher Harshaw
4. Yaron Singer
5. Marwa El Halabi
6. Moran Feldman
7. Amit Dhurandhar
8. Nina Grgic-Hlaca
9. Krishnateja Killamsetty
10. Guillermo A. Cecchi

Papers from Ethan R. Elenberg's perspective

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

Their papers

• Identifying Mislabeled Data using the Area Under the Margin Ranking (2020) — 378 citations
• Restricted Strong Convexity Implies Weak Submodularity (2016) — 165 citations
• Streaming Weak Submodularity: Interpreting Neural Networks on the Fly (2017) — 92 citations