Ya Li
Artificial Intelligence · with Liu · 2018
A researcher in the Science corpus: 3 papers; trusts 113 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 54 citations into it; #20,375 of 35,345 by trust here, #9,760 by citations
- Computer Vision and Pattern Recognition — 43 citations into it; #12,723 of 21,575 by trust here, #7,027 by citations
- Representation & Self-Supervised Learning — 37 citations into it
- Computational Mechanics — 8 citations into it
- Probabilistic & Bayesian Methods — 7 citations into it
- Statistics and Probability — 6 citations into it
Whom Ya Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Bernhard Schölkopf
- Kaiming He
- Yoshua Bengio
- Ilya Sutskever
- Yann LeCun
- Diederik P. Kingma
- Antonio Torralba
- Michael I. Jordan
Who trusts Ya Li overall
- Kaiyang Zhou
- Divyat Mahajan
- Yongxin Yang
- Bernhard Schölkopf
- Fengxiang He
- Toshihiko Matsuura
- Shruti Tople
- Tao A. Xiang
- Polina Kirichenko
- Yu Sun
Papers from Ya Li's perspective
Ordered by how strongly the researchers Ya Li 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Deep Domain Generalization via Conditional Invariant Adversarial Networks (2018) — 831 citations
- Domain Generalization via Conditional Invariant Representations (2018) — 305 citations
- On Better Exploring and Exploiting Task Relationships in Multitask Learning: Joint Model and Feature Learning (2018) — 45 citations