Haixuan Yang
Information Systems · 2008–2019
A researcher in the Science corpus: 4 papers; trusts 10 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 11 citations into it; #1,561 of 8,771 by trust here, #1,463 by citations
- Recommender Systems — 6 citations into it; #75 of 233 by trust here, #86 by citations
- Artificial Intelligence — 5 citations into it
Whom Haixuan Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Thomas Hofmann
- Ruslan Salakhutdinov
- Nati Srebro
- John F. Canny
- Paul Resnick
- Rong Jin
- Luo Si
- Andriy Mnih
- Jason D. M. Rennie
- Paolo Massa
Who trusts Haixuan Yang overall
- Xiwang Yang
- Huiji Gao
- Jiliang Tang
- Hao Ma
- Allison June-Barlow Chaney
- Hao Wang
- Weike Pan
- Sanjay Purushotham
- Qingyun Wu
- Qiang Yang
Papers from Haixuan Yang's perspective
Ordered by how strongly the researchers Haixuan Yang trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- SoRec: social recommendation using probabilistic matrix factorization (2008) — 1,565 citations
- A large-scale evaluation of computational protein function prediction (2013) — 1,002 citations
- A Census of Human Soluble Protein Complexes (2012) — 844 citations
- The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens (2019) — 434 citations