Jung-Su Ha

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 — 15 citations into it
• Reinforcement Learning — 11 citations into it
• Control and Systems Engineering — 10 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it
• Robotics & Control — 5 citations into it

Whom Jung-Su Ha trusts overall

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

1. Marc Toussaint
2. Chelsea Finn
3. Sergey Levine
4. Leslie Pack Kaelbling
5. Pieter Abbeel
6. Geoffrey E. Hinton
7. Diederik P. Kingma
8. Richard S. Sutton
9. Yoshua Bengio
10. Alex Krizhevsky

Papers from Jung-Su Ha's perspective

Ordered by how strongly the researchers Jung-Su Ha 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image (2020) — 116 citations