Haiyang Huang
Artificial Intelligence · with Rudin · 2020–2021
A researcher in the Science corpus: 2 papers; trusts 178 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 179 citations into it
- Computer Vision and Pattern Recognition — 88 citations into it
- Safety, Robustness & Interpretability — 68 citations into it
- Representation & Self-Supervised Learning — 58 citations into it
- Statistical Learning Theory — 36 citations into it
- Statistics and Probability — 34 citations into it
- Algorithms & Complexity — 28 citations into it
- Medical & Health AI — 27 citations into it
Whom Haiyang Huang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Cynthia Rudin
- Geoffrey E. Hinton
- L. V. D. van der Maaten
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Berk Ustun
- Yann LeCun
- Kaiming He
- Leo Breiman
Papers from Haiyang Huang's perspective
Ordered by how strongly the researchers Haiyang Huang 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
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)