Yazhe Li
Artificial Intelligence · 2016–2019
A researcher in the Science corpus: 5 papers; trusts 237 researchers and is trusted by 3,153 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 78 citations into it; #612 of 35,345 by trust here, #738 by citations
- Computer Vision and Pattern Recognition — 59 citations into it; #669 of 21,575 by trust here, #812 by citations
- Generative Models — 32 citations into it; #1,573 of 1,956 by trust here, #1,315 by citations
- Reinforcement Learning — 31 citations into it; #1,600 of 2,242 by trust here, #455 by citations
- Signal Processing — 22 citations into it; #4,988 of 7,572 by trust here, #261 by citations
- Natural Language Processing — 21 citations into it
- Representation & Self-Supervised Learning — 19 citations into it; #189 of 3,145 by trust here, #128 by citations
- Cognitive Neuroscience — 16 citations into it
Whom Yazhe Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Jimmy Ba
- Ilya Sutskever
- Kaiming He
- Yann LeCun
- Oriol Vinyals
- Alex Graves
Who trusts Yazhe Li overall
- Yoshua Bengio
- Yu-An Chung
- Sergey Levine
- Ruslan Salakhutdinov
- Pieter Abbeel
- Yonglong Tian
- Alexei Baevski
- Trevor Darrell
- Wei-Ning Hsu
- Zhe Gan
Papers from Yazhe Li's perspective
Ordered by how strongly the researchers Yazhe 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Representation Learning with Contrastive Predictive Coding (2018) — 13,907 citations
- Parallel WaveNet: Fast High-Fidelity Speech Synthesis (2017) — 912 citations
- Low Bit-rate Speech Coding with VQ-VAE and a WaveNet Decoder (2019) — 140 citations
- DeepMind Control Suite (2018) — 1,440 citations
- Model-Free Episodic Control (2016) — 289 citations