Yen-Chen Lin

Artificial Intelligence · 2017–2020

A researcher in the Science corpus: 4 papers; trusts 237 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 79 citations into it
• Computer Vision and Pattern Recognition — 70 citations into it
• Safety, Robustness & Interpretability — 32 citations into it
• Representation & Self-Supervised Learning — 21 citations into it
• Reinforcement Learning — 17 citations into it
• Control and Systems Engineering — 14 citations into it
• Natural Language Processing — 11 citations into it
• Optimization & Training — 5 citations into it

Whom Yen-Chen Lin trusts overall

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

1. Ian J. Goodfellow
2. Diederik P. Kingma
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Kaiming He
6. Christian Szegedy
7. Yoshua Bengio
8. Ilya Sutskever
9. Yann LeCun
10. Sergey Levine

Who trusts Yen-Chen Lin overall

1. Amal Feriani
2. A. Serban
3. Kenneth T. Co
4. Katja Auernhammer
5. Leo Gao
6. Kangle Deng
7. Chen-Hsuan Lin
8. Anay Pattanaik
9. Nilaksh Das
10. Matthew Tancik

Papers from Yen-Chen Lin's perspective

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

Their papers

• iNeRF: Inverting Neural Radiance Fields for Pose Estimation (2020) — 586 citations
• Tactics of Adversarial Attack on Deep Reinforcement Learning Agents (2017) — 474 citations
• Debiased Contrastive Learning (2020) — 739 citations
• Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight (2017) — 55 citations