Li Jing
Artificial Intelligence · 2016–2021
A researcher in the Science corpus: 4 papers; trusts 278 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 67 citations into it; #19,368 of 35,345 by trust here, #7,010 by citations
- Computer Vision and Pattern Recognition — 53 citations into it
- Representation & Self-Supervised Learning — 33 citations into it; #1,977 of 3,145 by trust here, #1,159 by citations
- Model Architectures — 17 citations into it
- Optimization & Training — 14 citations into it
Whom Li Jing trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Yann LeCun
- Yoshua Bengio
- Alex Krizhevsky
- Ross B. Girshick
- Ilya Sutskever
- Diederik P. Kingma
- Ishan Misra
- Xinlei Chen
Who trusts Li Jing overall
- Tri Dao
- Shaojie Bai
- Quang Pham
- Jie Gui
- Asier Mujika
- Divyam Madaan
- Arslan Chaudhry
- Eugene Vorontsov
- Valerio Marsocci
- Zewen Chi
Papers from Li Jing's perspective
Ordered by how strongly the researchers Li Jing 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Barlow Twins: Self-Supervised Learning via Redundancy Reduction (2021) — 3,100 citations
- Understanding Dimensional Collapse in Contrastive Self-supervised Learning (2021) — 496 citations
- Nanophotonic particle simulation and inverse design using artificial neural networks (2017) — 892 citations
- Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs (2016) — 191 citations