Harshay Shah

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 62 citations into it
• Safety, Robustness & Interpretability — 38 citations into it
• Computer Vision and Pattern Recognition — 26 citations into it
• Optimization & Training — 10 citations into it
• Model Architectures — 5 citations into it

Whom Harshay Shah trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Geoffrey E. Hinton
4. Nitish Srivastava
5. Alex Krizhevsky
6. Yoshua Bengio
7. Yann LeCun
8. Andrew L. Maas
9. Ilya Sutskever
10. Christian Szegedy

Who trusts Harshay Shah overall

1. Divyat Mahajan
2. Polina Kirichenko
3. Shruti Tople

Papers from Harshay Shah's perspective

Ordered by how strongly the researchers Harshay Shah 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
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. Going deeper with convolutions

Their papers

• The Pitfalls of Simplicity Bias in Neural Networks (2020) — 478 citations