Haoyi Xiong

Artificial Intelligence · 2016–2021

A researcher in the Science corpus: 5 papers; trusts 168 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 249 citations into it
• Computer Vision and Pattern Recognition — 92 citations into it
• Safety, Robustness & Interpretability — 72 citations into it
• Optimization & Training — 26 citations into it
• Model Architectures — 16 citations into it
• Electrical and Electronic Engineering — 11 citations into it
• Sociology and Political Science — 10 citations into it

Whom Haoyi Xiong trusts overall

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

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

Papers from Haoyi Xiong's perspective

Ordered by how strongly the researchers Haoyi Xiong 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. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• RIFLE: Backpropagation in Depth for Deep Transfer Learning through Re-Initializing the Fully-connected LayEr (2020) — 46 citations
• Structure-aware Interactive Graph Neural Networks for the Prediction of Protein-Ligand Binding Affinity (2021) — 231 citations
• Interpretable deep learning: interpretation, interpretability, trustworthiness, and beyond (2021) — 507 citations
• From distributed machine learning to federated learning: a survey (2021) — 358 citations
• Flood recovery and property acquisition in Cedar Rapids, Iowa (2016) — 134 citations