Zimin Chen
Artificial Intelligence · 2018–2021
A researcher in the Science corpus: 3 papers; trusts 28 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 58 citations into it
- Information Systems — 58 citations into it; #4,033 of 8,771 by trust here, #1,895 by citations
- Natural Language Processing — 47 citations into it
- Computer Vision and Pattern Recognition — 17 citations into it
- Model Architectures — 14 citations into it
- Code Generation & Program Synthesis — 13 citations into it
Whom Zimin Chen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Ilya Sutskever
- Oriol Vinyals
- Geoffrey E. Hinton
- Miltiadis Allamanis
- Sepp Hochreiter
- Kyunghyun Cho
- Diederik P. Kingma
- Dzmitry Bahdanau
- Alex Krizhevsky
Who trusts Zimin Chen overall
- Chun Xia
- Baptiste Rozière
- Michele Tufano
- Shaked Brody
- Michihiro Yasunaga
- Yangruibo Ding
- Yi Li
- Dawn Drain
- Julian Aron Prenner
- Hlib Babii
Papers from Zimin Chen's perspective
Ordered by how strongly the researchers Zimin Chen 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
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
Their papers
- PLUR: A Unifying, Graph-Based View of Program Learning, Understanding, and Repair (2021) — 29 citations
- Learning to Fix Build Errors with Graph2Diff Neural Networks (2019) — 70 citations
- SequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair (2018) — 554 citations