Jaesik Yoon

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it; #33,281 of 35,345 by trust here, #11,624 by citations
• Probabilistic & Bayesian Methods — 7 citations into it; #1,482 of 1,525 by trust here, #549 by citations
• Reinforcement Learning — 6 citations into it

Whom Jaesik Yoon trusts overall

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

1. Radford M. Neal
2. Ronald J. Williams
3. Geoffrey E. Hinton
4. Max Welling
5. Diederik P. Kingma
6. Yoshua Bengio
7. John Schulman
8. Chelsea Finn
9. Sergey Levine
10. Alex Krizhevsky

Who trusts Jaesik Yoon overall

1. Christopher Fifty
2. Tianhe Yu
3. Jake Snell
4. Louis Kirsch
5. Chang Liu

Papers from Jaesik Yoon's perspective

Ordered by how strongly the researchers Jaesik Yoon trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Bayesian Model-Agnostic Meta-Learning (2018) — 548 citations