Bairen Yi

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it
• Computer Vision and Pattern Recognition — 29 citations into it
• Optimization & Training — 22 citations into it
• Efficiency & Compression — 11 citations into it
• Model Architectures — 7 citations into it

Whom Bairen Yi trusts overall

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

1. Karen Simonyan
2. Kaiming He
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Ilya Sutskever
6. Andrew Zisserman
7. Alexander Sergeev
8. Yoshua Bengio
9. Diederik P. Kingma
10. X. Zhang

Papers from Bairen Yi's perspective

Ordered by how strongly the researchers Bairen Yi 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A generic communication scheduler for distributed DNN training acceleration (2019) — 407 citations
• A Unified Architecture for Accelerating Distributed DNN Training in Heterogeneous GPU/CPU Clusters (2020) — 410 citations