Isaac Monteath

Safety, Robustness & Interpretability · 2018

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Safety, Robustness & Interpretability — 15 citations into it
• Artificial Intelligence — 14 citations into it

Whom Isaac Monteath trusts overall

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

1. J. Urgen Schmidhuber
2. Finale Doshi-Velez
3. Andrew Slavin Ross
4. Tim Miller
5. Sebastian Bach
6. Geoffrey E. Hinton
7. David Silver
8. Been Kim
9. Richard S. Sutton

Papers from Isaac Monteath's perspective

Ordered by how strongly the researchers Isaac Monteath 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. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Defining Explainable AI for Requirements Analysis (2018) — 42 citations