Yuanpeng Li
Artificial Intelligence · 2019–2020
A researcher in the Science corpus: 3 papers; trusts 34 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 34 citations into it
- Computer Vision and Pattern Recognition — 22 citations into it
- Model Architectures — 13 citations into it
- Natural Language Processing — 11 citations into it; #4,165 of 5,688 by trust here, #3,369 by citations
- Cognitive Science & Psychology — 7 citations into it
- Cognitive Neuroscience — 6 citations into it
Whom Yuanpeng Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Brenden M. Lake
- Ilya Sutskever
- Oriol Vinyals
- Geoffrey E. Hinton
- Alex Krizhevsky
- Marco Baroni
- Yoshua Bengio
- Diederik P. Kingma
- Kaiming He
- Yann LeCun
Who trusts Yuanpeng Li overall
- Zixuan Ke
- Jorge Armando Mendez Mendez
- Peter Shaw
- Xinyun Chen
- Yijia Shao
- Eric Eaton
- Haowei Lin
- Ming-Wei Chang
- Alon Talmor
- Xisen Jin
Papers from Yuanpeng Li's perspective
Ordered by how strongly the researchers Yuanpeng 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)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Compositional Continual Language Learning (2020) — 8 citations
- Compositional Generalization for Primitive Substitutions (2019) — 89 citations
- Compositional Language Continual Learning (2019) — 40 citations