Wenbing Huang

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 9 papers; trusts 709 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 192 citations into it; #29,895 of 35,345 by trust here, #5,281 by citations
• Computer Vision and Pattern Recognition — 192 citations into it; #18,353 of 21,575 by trust here, #4,212 by citations
• Representation & Self-Supervised Learning — 52 citations into it
• Graph Learning — 42 citations into it
• Model Architectures — 28 citations into it
• Natural Language Processing — 23 citations into it
• Optimization & Training — 20 citations into it
• Evaluation & Benchmarks — 15 citations into it

Whom Wenbing Huang trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Ross B. Girshick
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Yoshua Bengio
7. Karen Simonyan
8. Yann LeCun
9. Andrew Zisserman
10. Ilya Sutskever

Who trusts Wenbing Huang overall

1. Huayao Liu
2. Yanqiao Zhu
3. Zhengyuan Yang
4. Guohao Li
5. Chen Zhao
6. Shaked Brody
7. Chen-Lin Zhang
8. Qitian Wu
9. Yong Guo
10. Ruosong Ye

Papers from Wenbing Huang's perspective

Ordered by how strongly the researchers Wenbing Huang 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. 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. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A Fast and Accurate One-Stage Approach to Visual Grounding (2019) — 449 citations
• Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering (2019) — 299 citations
• Progressive Feature Alignment for Unsupervised Domain Adaptation (2018) — 481 citations
• DropEdge: Towards Deep Graph Convolutional Networks on Node Classification (2019) — 1,663 citations
• Graph Convolutional Networks for Temporal Action Localization (2019) — 542 citations
• Deep Multimodal Fusion by Channel Exchanging (2020) — 310 citations
• Graph Representation Learning via Graphical Mutual Information Maximization (2020) — 693 citations
• Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks (2020) — 816 citations
• Dense Regression Network for Video Grounding (2020) — 339 citations