Raymond Ka-Man Sheh

Safety, Robustness & Interpretability · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Safety, Robustness & Interpretability — 17 citations into it
• Artificial Intelligence — 14 citations into it

Whom Raymond Ka-Man Sheh trusts overall

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

1. J. Urgen Schmidhuber
2. Aude Gemma Billard
3. Finale Doshi-Velez
4. Andrew Slavin Ross
5. Tim Miller
6. Marco Tulio Ribeiro
7. J. Ross Quinlan
8. M. Rey
9. Sebastian Bach
10. Geoffrey E. Hinton

Who trusts Raymond Ka-Man Sheh overall

1. Shane T. Mueller

Papers from Raymond Ka-Man Sheh's perspective

Ordered by how strongly the researchers Raymond Ka-Man Sheh 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Defining Explainable AI for Requirements Analysis (2018) — 42 citations
• "Why Did You Do That?" Explainable Intelligent Robots (2017) — 40 citations