Dongsheng Li

Artificial Intelligence · with Li · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 19 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 38 citations into it
• Computer Vision and Pattern Recognition — 29 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Generative Models — 7 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Dongsheng Li trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yann LeCun
4. Yoshua Bengio
5. Max Welling
6. Diederik P. Kingma
7. Kaiming He
8. Christian Szegedy

Papers from Dongsheng Li's perspective

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

Their papers

• Finding Global Homophily in Graph Neural Networks When Meeting Heterophily (2022) — 296 citations
• Energy-Based Open-World Uncertainty Modeling for Confidence Calibration (2021) — 80 citations