Toru Lin

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 38 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it
• Computer Vision and Pattern Recognition — 26 citations into it
• Reinforcement Learning — 23 citations into it
• Control and Systems Engineering — 13 citations into it
• Statistical and Nonlinear Physics — 5 citations into it

Whom Toru Lin trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. E. Todorov
4. Yoshua Bengio
5. Igor Mordatch
6. Sergey Levine
7. Yilun Du
8. J. Urgen Schmidhuber
9. Alex Krizhevsky
10. Yann LeCun

Papers from Toru Lin's perspective

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

Their papers

• Visual Grounding of Learned Physical Models (2020) — 90 citations
• Model Based Planning with Energy Based Models (2019) — 44 citations