Yibo Li

Computational Theory and Mathematics · with Lai · 2018–2021

A researcher in the Science corpus: 2 papers; trusts 46 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 37 citations into it; #5,898 of 12,182 by trust here, #3,117 by citations
• Molecular Biology — 27 citations into it
• Artificial Intelligence — 24 citations into it
• Computational Chemistry & Drug Discovery — 21 citations into it
• Materials Chemistry — 19 citations into it
• Computer Vision and Pattern Recognition — 18 citations into it
• Generative Models — 18 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Yibo Li trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Kaiming He
4. Yoshua Bengio
5. Hans-Joachim Böhm
6. Daniel D. Johnson
7. Yann LeCun
8. Max Welling
9. Alex Krizhevsky
10. L. V. D. van der Maaten

Who trusts Yibo Li overall

1. Nicola De Cao
2. Tânia F Cova
3. Jaehyeong Jo
4. Chenhao Niu
5. Renjie Liao
6. Thomas Kipf
7. A. Pais
8. Yang Song
9. Yuanqi Du
10. Seul Lee

Papers from Yibo Li's perspective

Ordered by how strongly the researchers Yibo Li 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. 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. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Multi-objective de novo drug design with conditional graph generative model (2018) — 401 citations
• Structure-based de novo drug design using 3D deep generative models (2021) — 150 citations