Zekun Yang
Artificial Intelligence · 2019–2020
A researcher in the Science corpus: 2 papers; trusts 82 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 47 citations into it
- Natural Language Processing — 30 citations into it
- Computer Vision and Pattern Recognition — 29 citations into it
- Representation & Self-Supervised Learning — 12 citations into it
- Evaluation & Benchmarks — 7 citations into it
- Safety, Robustness & Interpretability — 7 citations into it
Whom Zekun Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Richard Socher
- Kaiming He
- Sepp Hochreiter
- Diederik P. Kingma
- Alex Krizhevsky
- Ilya Sutskever
- Jeffrey Pennington
- Yann LeCun
Who trusts Zekun Yang overall
- Devshree Patel
- Suraj Nair
- Yuren Cong
- Seonhoon Kim
- Xudong Lin
- Jesse Vig
- Gedas Bertasius
- Ratnam Parikh
Papers from Zekun Yang's perspective
Ordered by how strongly the researchers Zekun Yang trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- BERT Representations for Video Question Answering (2020) — 118 citations
- A Causal Inference Method for Reducing Gender Bias in Word Embedding Relations (2019) — 41 citations