Hui-jun Han

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it
• Computer Vision and Pattern Recognition — 13 citations into it
• Representation & Self-Supervised Learning — 12 citations into it
• Statistical and Nonlinear Physics — 12 citations into it
• Graph Learning — 7 citations into it
• Molecular Biology — 5 citations into it

Whom Hui-jun Han trusts overall

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

1. Diederik P. Kingma
2. Thomas Kipf
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Max Welling
6. Kaiming He
7. Ralph Linsker
8. Xavier Glorot
9. Jimmy Ba
10. Alex Krizhevsky

Papers from Hui-jun Han's perspective

Ordered by how strongly the researchers Hui-jun Han trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning (2021) — 542 citations