Yujin Tang
Artificial Intelligence · 2020–2022
A researcher in the Science corpus: 2 papers; trusts 343 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 68 citations into it
- Computer Vision and Pattern Recognition — 57 citations into it
- Reinforcement Learning — 27 citations into it
- Meta & Continual Learning — 23 citations into it
- Model Architectures — 17 citations into it
- Representation & Self-Supervised Learning — 11 citations into it
- Cognitive Neuroscience — 9 citations into it
- Optimization & Training — 9 citations into it
Whom Yujin Tang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- J. Urgen Schmidhuber
- Geoffrey E. Hinton
- Kaiming He
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Yann LeCun
- Sepp Hochreiter
- Alex Graves
Who trusts Yujin Tang overall
Papers from Yujin Tang's perspective
Ordered by how strongly the researchers Yujin Tang 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
- 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
- Neuroevolution of self-interpretable agents (2020) — 119 citations
- Learning to Imagine: Diversify Memory for Incremental Learning using Unlabeled Data (2022) — 37 citations