Todd P. Huster

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it; #21,713 of 35,345 by trust here, #28,481 by citations
• Safety, Robustness & Interpretability — 12 citations into it

Whom Todd P. Huster trusts overall

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

1. Anish Athalye
2. Aditi Raghunathan
3. Nicholas Carlini
4. Yusuke Tsuzuku
5. Alex Krizhevsky
6. Geoffrey E. Hinton
7. Ian J. Goodfellow
8. Christian Szegedy
9. Ilya Sutskever
10. David A. Wagner

Who trusts Todd P. Huster overall

1. Klas Leino
2. A. Serban
3. Yao-Yuan Yang
4. Zifan Wang
5. Erik Poll
6. Cyrus Rashtchian

Papers from Todd P. Huster's perspective

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

Their papers

• Limitations of the Lipschitz constant as a defense against adversarial examples (2018) — 90 citations