Erica Schmidt

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 885 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 148 citations into it
• Computer Vision and Pattern Recognition — 129 citations into it
• Representation & Self-Supervised Learning — 50 citations into it
• Natural Language Processing — 38 citations into it
• Model Architectures — 23 citations into it
• Generative Models — 22 citations into it
• Molecular Biology — 20 citations into it
• Safety, Robustness & Interpretability — 20 citations into it

Whom Erica Schmidt trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Alex Krizhevsky
5. Kaiming He
6. Karen Simonyan
7. Ilya Sutskever
8. Yann LeCun
9. Ross B. Girshick
10. Alex Graves

Papers from Erica Schmidt's perspective

Ordered by how strongly the researchers Erica Schmidt 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• A Survey of Deep Learning for Scientific Discovery (2020) — 155 citations