Jae-Kyo Noh

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it
• Reinforcement Learning — 11 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Jae-Kyo Noh trusts overall

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

1. Martin L. Puterman
2. Carl Doersch
3. Deborah A. Maranville
4. Ronald H. W. Hoppe

Papers from Jae-Kyo Noh's perspective

Ordered by how strongly the researchers Jae-Kyo Noh trusts endorse each paper. Same corpus, a different order for every researcher.

1. Playing Atari with Deep Reinforcement Learning (arXiv.org)
2. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Markov Decision Processes: Discrete Stochastic Dynamic Programming
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Deep learning enabled inverse design in nanophotonics (2020) — 473 citations