Shao Kun Deng
Information Systems · 2020–2022
A researcher in the Science corpus: 5 papers; trusts 32 researchers and is trusted by 17 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 110 citations into it; #1,779 of 8,771 by trust here, #254 by citations
- Artificial Intelligence — 104 citations into it; #11,637 of 35,345 by trust here, #7,657 by citations
- Natural Language Processing — 99 citations into it
- Software — 69 citations into it; #239 of 1,227 by trust here, #19 by citations
- Code Generation & Program Synthesis — 51 citations into it
- Evaluation & Benchmarks — 28 citations into it
- Computer Vision and Pattern Recognition — 26 citations into it
- Computer Networks and Communications — 13 citations into it
Whom Shao Kun Deng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Chin-Yew Lin
- Michele Tufano
- Premkumar T. Devanbu
- Geoffrey E. Hinton
- Jimmy Ba
- Ashish Vaswani
- René Just
- Yoshua Bengio
- Carlos Pacheco
- Alexey Svyatkovskiy
Who trusts Shao Kun Deng overall
- Daya Guo
- Yue Wang
- Xinyun Chen
- Yichen Xu
- Colin B. Clement
- Vincent J. Hellendoorn
- Hung Le
- Tianyang Liu
- Shuai Lu
- Fengji Zhang
Papers from Shao Kun Deng's perspective
Ordered by how strongly the researchers Shao Kun Deng trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
Their papers
- IntelliCode compose: code generation using transformer (2020) — 626 citations
- GraphCodeBERT: Pre-training Code Representations with Data Flow (2020) — 1,778 citations
- METHODS2TEST: A dataset of focal methods mapped to test cases (2022) — 45 citations
- CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation (2021) — 1,545 citations
- Unit Test Case Generation with Transformers (2020) — 292 citations