Hao Fang
Artificial Intelligence · with Cheng · 2014–2020
A researcher in the Science corpus: 7 papers; trusts 207 researchers and is trusted by 1,416 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 149 citations into it; #15,034 of 35,345 by trust here, #2,822 by citations
- Natural Language Processing — 131 citations into it
- Computer Vision and Pattern Recognition — 101 citations into it; #1,094 of 21,575 by trust here, #909 by citations
- Representation & Self-Supervised Learning — 28 citations into it
- Evaluation & Benchmarks — 27 citations into it; #584 of 3,147 by trust here, #321 by citations
- Model Architectures — 24 citations into it
- Large Language Models — 9 citations into it
- Optimization & Training — 8 citations into it
Whom Hao Fang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Ross B. Girshick
- Richard Socher
- Ilya Sutskever
- Karen Simonyan
- Diederik P. Kingma
- Kaiming He
- Yann LeCun
Who trusts Hao Fang overall
- Zhe Gan
- Mohit Bansal
- Qi Wu
- Jiasen Lu
- Peter Anderson
- Ting Yao
- Ishan Misra
- Yi Yang
- Jianfeng Gao
- Yoshua Bengio
Papers from Hao Fang's perspective
Ordered by how strongly the researchers Hao Fang trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- 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
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Microsoft COCO Captions: Data Collection and Evaluation Server (2015) — 2,946 citations
- From captions to visual concepts and back (2014) — 1,357 citations
- Language Models for Image Captioning: The Quirks and What Works (2015) — 293 citations
- Task-Oriented Dialogue as Dataflow Synthesis (2020) — 176 citations
- Sounding Board: A User-Centric and Content-Driven Social Chatbot (2018) — 61 citations
- Open-Domain Name Error Detection using a Multi-Task RNN (2015) — 48 citations
- Conference on Empirical Methods in Natural Language Processing Proceedings of the Fourth International Workshop on Natural Language Processing for Social Media Socialnlp@emnlp2016 Chairs' Welcome Identifying and Categorizing Disaster-related Tweets Why Do They Leave: Modeling Participation in Online