Li Gu
Artificial Intelligence · with Wang · 2018–2022
A researcher in the Science corpus: 3 papers; trusts 58 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 66 citations into it
- Computer Vision and Pattern Recognition — 53 citations into it
- Representation & Self-Supervised Learning — 21 citations into it
- Probabilistic & Bayesian Methods — 16 citations into it
- Generative Models — 10 citations into it
- Safety, Robustness & Interpretability — 10 citations into it
Whom Li Gu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Kaiming He
- Diederik P. Kingma
- Yoshua Bengio
- Yann LeCun
- Alex Graves
- Ilya Sutskever
- Max Welling
- Karen Simonyan
Who trusts Li Gu overall
Papers from Li Gu's perspective
Ordered by how strongly the researchers Li Gu 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- MetaFSCIL: A Meta-Learning Approach for Few-Shot Class Incremental Learning (2022) — 188 citations
- Few-Shot Class-Incremental Learning via Entropy-Regularized Data-Free Replay (2022) — 137 citations
- Adversarial Distillation of Bayesian Neural Network Posteriors (2018) — 61 citations