Yichen Jiang
Artificial Intelligence · 2019
A researcher in the Science corpus: 3 papers; trusts 488 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 76 citations into it; #7,014 of 35,345 by trust here, #13,353 by citations
- Natural Language Processing — 60 citations into it; #1,534 of 5,688 by trust here, #2,846 by citations
- Computer Vision and Pattern Recognition — 44 citations into it; #5,481 of 21,575 by trust here, #9,187 by citations
- Evaluation & Benchmarks — 22 citations into it
- Information Retrieval & Search — 17 citations into it
- Model Architectures — 13 citations into it; #1,565 of 2,278 by trust here, #1,927 by citations
- Representation & Self-Supervised Learning — 5 citations into it
Whom Yichen Jiang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Sepp Hochreiter
- Yoshua Bengio
- Geoffrey E. Hinton
- J. Urgen Schmidhuber
- Richard Socher
- Jimmy Ba
- Ronald J. Williams
- Alex Krizhevsky
- Christopher D. Manning
Who trusts Yichen Jiang overall
- Ethan Perez
- Xi Ye
- Greg Durrett
- Qinyuan Ye
- Viktor Schlegel
- Douwe Kiela
- Tomer Wolfson
- Patrick Lewis
- Kyunghyun Cho
- Chen Zhao
Papers from Yichen Jiang's perspective
Ordered by how strongly the researchers Yichen Jiang 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Avoiding Reasoning Shortcuts: Adversarial Evaluation, Training, and Model Development for Multi-Hop QA (2019) — 113 citations
- Self-Assembling Modular Networks for Interpretable Multi-Hop Reasoning (2019) — 74 citations
- Explore, Propose, and Assemble: An Interpretable Model for Multi-Hop Reading Comprehension (2019) — 42 citations