Haotian Fu

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it
• Reinforcement Learning — 25 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it

Whom Haotian Fu trusts overall

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

1. Geoffrey E. Hinton
2. J. Urgen Schmidhuber
3. Pieter Abbeel
4. Kaiming He
5. Yoshua Bengio
6. Diederik P. Kingma
7. Alex Krizhevsky
8. Sergey Levine
9. Richard S. Sutton
10. Volodymyr Mnih

Papers from Haotian Fu's perspective

Ordered by how strongly the researchers Haotian Fu 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. 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning (2020) — 61 citations
• Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces (2019) — 84 citations