Jack Koch

Artificial Intelligence · 2021

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

Subfields

• Artificial Intelligence — 25 citations into it
• Safety, Robustness & Interpretability — 14 citations into it

Whom Jack Koch trusts overall

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

1. Joseph B. Kruskal
2. Martín Arjovsky
3. John Schulman
4. Geoffrey E. Hinton
5. Ian J. Goodfellow
6. Diederik P. Kingma
7. Richard S. Sutton
8. L. Eon Bottou
9. Yoshua Bengio
10. Christian Szegedy

Papers from Jack Koch's perspective

Ordered by how strongly the researchers Jack Koch 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Objective Robustness in Deep Reinforcement Learning (2021) — 16 citations