Amy X. Lu

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 55 citations into it
• Representation & Self-Supervised Learning — 33 citations into it
• Molecular Biology — 24 citations into it
• Safety, Robustness & Interpretability — 23 citations into it
• Computer Vision and Pattern Recognition — 19 citations into it
• Natural Language Processing — 19 citations into it
• Computational Biology & Bioinformatics — 17 citations into it

Whom Amy X. Lu trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Diederik P. Kingma
4. David John Cameron MacKay
5. Yoshua Bengio
6. Alex Krizhevsky
7. Ilya Sutskever
8. Yann LeCun
9. Ross B. Girshick
10. Radford M. Neal

Who trusts Amy X. Lu overall

1. Pascal Sturmfels
2. Zuobai Zhang
3. Pranav Rajpurkar
4. Silvio Amir
5. Jesse Vig
6. Mohammed Saeed

Papers from Amy X. Lu's perspective

Ordered by how strongly the researchers Amy X. Lu 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. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Self-Supervised Contrastive Learning of Protein Representations By Mutual Information Maximization (2020) — 93 citations
• Hurtful words: quantifying biases in clinical contextual word embeddings (2020) — 206 citations