Jake Olkin

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it
• Control and Systems Engineering — 24 citations into it
• Reinforcement Learning — 22 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it

Whom Jake Olkin trusts overall

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

1. Reuven Y. Rubinstein
2. Diederik P. Kingma
3. Pieter Abbeel
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Mitul Saha

Papers from Jake Olkin's perspective

Ordered by how strongly the researchers Jake Olkin 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Human-level control through deep reinforcement learning
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation

Their papers

• SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation (2020) — 291 citations