Chaofan Tao
Artificial Intelligence · 2018–2022
A researcher in the Science corpus: 3 papers; trusts 200 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 89 citations into it
- Computer Vision and Pattern Recognition — 70 citations into it; #18,258 of 21,575 by trust here, #18,266 by citations
- Model Architectures — 12 citations into it
- Representation & Self-Supervised Learning — 12 citations into it
Whom Chaofan Tao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Kaiming He
- Diederik P. Kingma
- Karen Simonyan
- Alex Krizhevsky
- Ross B. Girshick
- Yann LeCun
- Ilya Sutskever
- Tomas Mikolov
Who trusts Chaofan Tao overall
Papers from Chaofan Tao's perspective
Ordered by how strongly the researchers Chaofan Tao 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)
- 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
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Compression of Generative Pre-trained Language Models via Quantization (2022) — 119 citations
- A case-based interpretable deep learning model for classification of mass lesions in digital mammography (2021) — 193 citations
- This Looks Like That: Deep Learning for Interpretable Image Recognition (2018)