Haochen Chen

Artificial Intelligence · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 25 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it; #29,339 of 35,345 by trust here, #19,439 by citations
• Representation & Self-Supervised Learning — 19 citations into it
• Graph Learning — 15 citations into it
• Statistical and Nonlinear Physics — 9 citations into it; #8,088 of 10,127 by trust here, #4,137 by citations
• Computer Vision and Pattern Recognition — 7 citations into it
• Natural Language Processing — 7 citations into it

Whom Haochen Chen trusts overall

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

1. Chris Walshaw
2. Tomas Mikolov
3. Bryan Perozzi
4. Sam T. Roweis
5. Mikhail Belkin
6. Yoav Goldberg
7. Shaosheng Cao
8. Rong-En Fan
9. Ilya Sutskever
10. Geoffrey E. Hinton

Who trusts Haochen Chen overall

1. Yassine Ouali
2. Daokun Zhang
3. Xiao Liu
4. Benedek Rozemberczki
5. Sami Abu-El-Haija
6. Céline Hudelot
7. Bryan Perozzi
8. Jie Yin

Papers from Haochen Chen's perspective

Ordered by how strongly the researchers Haochen Chen 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• HARP: Hierarchical Representation Learning for Networks (2017) — 392 citations
• Don't Walk, Skip!: Online Learning of Multi-scale Network Embeddings (2016) — 204 citations