Leslie Rice

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 147 researchers and is trusted by 38 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 89 citations into it; #5,752 of 35,345 by trust here, #10,566 by citations
• Safety, Robustness & Interpretability — 85 citations into it; #840 of 2,251 by trust here, #1,220 by citations
• Computer Vision and Pattern Recognition — 30 citations into it
• Molecular Biology — 18 citations into it
• Optimization & Training — 12 citations into it
• Hardware and Architecture — 10 citations into it
• Program Analysis & Verification — 9 citations into it
• Signal Processing — 8 citations into it; #2,321 of 7,572 by trust here, #2,114 by citations

Whom Leslie Rice trusts overall

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

1. Ian J. Goodfellow
2. Kaiming He
3. Nicholas Carlini
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Christian Szegedy
7. Yoshua Bengio
8. Eric Wong
9. Diederik P. Kingma
10. Yann LeCun

Who trusts Leslie Rice overall

1. Sven Gowal
2. Tianyu Pang
3. Maksym Andriushchenko
4. Jingfeng Zhang
5. A. Serban
6. Sylvestre-Alvise Rebuffi
7. Anqi Mao
8. Dongxian Wu
9. Cihang Xie
10. Eric Wong

Papers from Leslie Rice's perspective

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

Their papers

• Fast is better than free: Revisiting adversarial training (2020) — 1,385 citations
• Overfitting in adversarially robust deep learning (2020) — 962 citations