Yuhao Zhang
Artificial Intelligence · with Manning · 2017–2021
A researcher in the Science corpus: 8 papers; trusts 390 researchers and is trusted by 42 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 176 citations into it; #7,272 of 35,345 by trust here, #4,231 by citations
- Natural Language Processing — 112 citations into it; #1,152 of 5,688 by trust here, #1,102 by citations
- Computer Vision and Pattern Recognition — 85 citations into it; #7,941 of 21,575 by trust here, #4,502 by citations
- Evaluation & Benchmarks — 42 citations into it
- Model Architectures — 25 citations into it
- Multimodal Learning — 25 citations into it; #1,080 of 1,211 by trust here, #583 by citations
- Representation & Self-Supervised Learning — 25 citations into it; #3,077 of 3,145 by trust here, #1,415 by citations
- Molecular Biology — 19 citations into it
Whom Yuhao Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Christopher D. Manning
- Diederik P. Kingma
- Yoshua Bengio
- Kaiming He
- Alex Krizhevsky
- Ilya Sutskever
- Ronald J. Williams
- Yann LeCun
- Richard Socher
Who trusts Yuhao Zhang overall
- Christoph Alt
- Xu Han
- Zhijiang Guo
- Michihiro Yasunaga
- Xisen Jin
- Wenxuan Zhou
- Percy Liang
- Peng Shi
- Guoshun Nan
- Zhiyuan Liu
Papers from Yuhao Zhang's perspective
Ordered by how strongly the researchers Yuhao Zhang 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- 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)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Contrastive Learning of Medical Visual Representations from Paired Images and Text (2020) — 1,105 citations
- Stanza: A Python Natural Language Processing Toolkit for Many Human Languages (2020) — 2,124 citations
- Position-aware Attention and Supervised Data Improve Slot Filling (2017) — 979 citations
- Graph Convolution over Pruned Dependency Trees Improves Relation Extraction (2018) — 796 citations
- Optimizing the Factual Correctness of a Summary: A Study of Summarizing Radiology Reports (2019) — 210 citations
- Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation (2020) — 235 citations
- Learning to Summarize Radiology Findings (2018) — 139 citations
- RadGraph: Extracting Clinical Entities and Relations from Radiology Reports (2021) — 435 citations