Patrick Schwab

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 40 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it; #24,610 of 35,345 by trust here, #27,551 by citations
• Safety, Robustness & Interpretability — 23 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it
• Model Architectures — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Patrick Schwab trusts overall

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

1. Yarin Gal
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Nitish Srivastava
6. Yoshua Bengio
7. Ilya Sutskever
8. Pang Wei Koh
9. Scott M. Lundberg
10. Yann LeCun

Who trusts Patrick Schwab overall

1. Ian Covert
2. Matthew R. O'Shaughnessy
3. Scott M. Lundberg
4. Gregory H. Canal
5. Stephan Alaniz
6. Su-In Lee
7. Aida Mostafazadeh Davani

Papers from Patrick Schwab's perspective

Ordered by how strongly the researchers Patrick Schwab trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• CXPlain: Causal Explanations for Model Interpretation under Uncertainty (2019) — 247 citations