Samuel Cohen

2022

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

Whom Samuel Cohen trusts overall

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

1. Yang Song
2. Cédric Villani
3. Jonathan Ho
4. Diederik P. Kingma

Papers from Samuel Cohen's perspective

Ordered by how strongly the researchers Samuel Cohen 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Variational Inference with Normalizing Flows
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Long Short-Term Memory
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Matching Normalizing Flows and Probability Paths on Manifolds (2022) — 64 citations