Lisa Amini

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 2 papers; trusts 96 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 73 citations into it
• Computer Vision and Pattern Recognition — 45 citations into it
• Safety, Robustness & Interpretability — 26 citations into it
• Representation & Self-Supervised Learning — 22 citations into it
• Optimization & Training — 12 citations into it
• Meta & Continual Learning — 11 citations into it
• Model Architectures — 7 citations into it

Whom Lisa Amini trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Antonio Torralba
6. Ross B. Girshick
7. Yann LeCun
8. Diederik P. Kingma
9. X. Zhang
10. Ian J. Goodfellow

Papers from Lisa Amini's perspective

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

Their papers

• Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning (2020) — 295 citations
• Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning (2022) — 7 citations