Chris Watkins

Artificial Intelligence · 1999–2019

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Safety, Robustness & Interpretability — 12 citations into it

Whom Chris Watkins trusts overall

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

1. Diederik P. Kingma
2. Ian J. Goodfellow
3. Christian Szegedy
4. Scott M. Lundberg
5. Vladimir Naumovich Vapni
6. Alexey Kurakin

Who trusts Chris Watkins overall

1. Koby Crammer
2. Johannes Fürnkranz
3. Lior Rokach
4. Harish Guruprasad Ramaswamy
5. Timo Schick
6. Hui Jiang
7. Lifeng Wang
8. Andrea Pohoreckyj Danyluk
9. Lin Xiao
10. Maya R. Gupta

Papers from Chris Watkins's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Intriguing properties of neural networks
5. Gradient-based learning applied to document recognition
6. Explaining and Harnessing Adversarial Examples
7. Long Short-Term Memory
8. ImageNet Large Scale Visual Recognition Challenge
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Explaining Deep Learning Models with Constrained Adversarial Examples (2019) — 45 citations
• Support vector machines for multi-class pattern recognition (1999)