Da Li
Computer Vision and Pattern Recognition · with Hospedales · 2017–2020
A researcher in the Science corpus: 5 papers; trusts 560 researchers and is trusted by 79 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 122 citations into it; #4,242 of 21,575 by trust here, #4,174 by citations
- Artificial Intelligence — 104 citations into it; #2,915 of 35,345 by trust here, #3,957 by citations
- Representation & Self-Supervised Learning — 48 citations into it; #552 of 3,145 by trust here, #645 by citations
- Reinforcement Learning — 16 citations into it
- Optimization & Training — 14 citations into it
- Evaluation & Benchmarks — 9 citations into it
- Radiology, Nuclear Medicine and Imaging — 9 citations into it
- Safety, Robustness & Interpretability — 9 citations into it
Whom Da Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Kaiming He
- Diederik P. Kingma
- Yoshua Bengio
- Ilya Sutskever
- Yann LeCun
- Christian Szegedy
- Ross B. Girshick
- Antonio Torralba
Who trusts Da Li overall
- Kaiyang Zhou
- Yongxin Yang
- Haohan Wang
- Timothy M. Hospedales
- Qi-Yan Dou
- Tao A. Xiang
- Hyeonseob Nam
- Divyat Mahajan
- Fabio Maria Carlucci
- Ishaan Gulrajani
Papers from Da Li's perspective
Ordered by how strongly the researchers Da Li 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)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Deeper, Broader and Artier Domain Generalization (2017) — 1,792 citations
- Episodic Training for Domain Generalization (2019) — 499 citations
- Learning to Generalize: Meta-Learning for Domain Generalization (2017) — 1,757 citations
- Robust Person Re-Identification by Modelling Feature Uncertainty (2019) — 152 citations
- Sketch-a-Segmenter: Sketch-Based Photo Segmenter Generation (2020) — 18 citations