Kaizhao Liang
Artificial Intelligence · 2019–2021
A researcher in the Science corpus: 3 papers; trusts 104 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 110 citations into it
- Computer Vision and Pattern Recognition — 66 citations into it
- Model Architectures — 19 citations into it
- Safety, Robustness & Interpretability — 16 citations into it
- Scaling & Learning Theory — 16 citations into it
- Optimization & Training — 13 citations into it
- Generative Models — 5 citations into it
Whom Kaizhao Liang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Kaiming He
- Alex Krizhevsky
- Yoshua Bengio
- Yann LeCun
- Karen Simonyan
- Ilya Sutskever
- Jia Deng
- Ian J. Goodfellow
Papers from Kaizhao Liang's perspective
Ordered by how strongly the researchers Kaizhao Liang 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)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- 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
- NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation (2021) — 104 citations
- Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models (2021) — 95 citations
- Big but Imperceptible Adversarial Perturbations via Semantic Manipulation (2019) — 28 citations