Ye Zhang

Artificial Intelligence · with Wallace · 2001–2019

A researcher in the Science corpus: 9 papers; trusts 268 researchers and is trusted by 61 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 210 citations into it; #4,977 of 35,345 by trust here, #6,720 by citations
• Natural Language Processing — 138 citations into it; #1,242 of 5,688 by trust here, #2,263 by citations
• Computer Vision and Pattern Recognition — 61 citations into it; #4,393 of 21,575 by trust here, #8,722 by citations
• Representation & Self-Supervised Learning — 41 citations into it
• Information Systems — 37 citations into it; #6,875 of 8,771 by trust here, #7,107 by citations
• Model Architectures — 30 citations into it; #973 of 2,278 by trust here, #1,530 by citations
• Optimization & Training — 17 citations into it
• Computational Theory and Mathematics — 13 citations into it; #11,403 of 12,182 by trust here, #5,724 by citations

Whom Ye Zhang trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Tomas Mikolov
4. Ilya Sutskever
5. Yoon Kim
6. Alex Krizhevsky
7. Matthew D. Zeiler
8. Yann LeCun
9. Diederik P. Kingma
10. Ronan Collobert

Who trusts Ye Zhang overall

1. Byron C. Wallace
2. Jean-Philippe Pons
3. Matthew Lease
4. Kezban Dilek Onal
5. Tom Young
6. Iain James Marshall
7. Peter Hase
8. John Pavlopoulos
9. Michael Hornacek
10. Xingyou Wang

Papers from Ye Zhang's perspective

Ordered by how strongly the researchers Ye Zhang 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• On 3D scene flow and structure estimation (2001) — 93 citations
• A Sensitivity Analysis of (and Practitioners’ Guide to) Convolutional Neural Networks for Sentence Classification (2015) — 1,309 citations
• Rationale-Augmented Convolutional Neural Networks for Text Classification (2016) — 172 citations
• Do Human Rationales Improve Machine Explanations? (2019) — 64 citations
• Fast and Secure Three-party Computation: The Garbled Circuit Approach (2015) — 123 citations
• On the second-order asymptotical regularization of linear ill-posed inverse problems (2018) — 66 citations
• Exploiting Domain Knowledge via Grouped Weight Sharing with Application to Text Categorization (2017) — 15 citations
• Neural information retrieval: at the end of the early years (2017) — 138 citations
• MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification (2016) — 110 citations