Kry Yik-Chau Lui
Artificial Intelligence · 2018
A researcher in the Science corpus: 3 papers; trusts 81 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 59 citations into it; #34,637 of 35,345 by trust here, #18,586 by citations
- Safety, Robustness & Interpretability — 41 citations into it; #2,167 of 2,251 by trust here, #1,589 by citations
- Computer Vision and Pattern Recognition — 37 citations into it
- Optimization & Training — 10 citations into it
- Signal Processing — 8 citations into it
- Molecular Biology — 5 citations into it
- Statistical and Nonlinear Physics — 5 citations into it
Whom Kry Yik-Chau Lui trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Ian J. Goodfellow
- Diederik P. Kingma
- Yoshua Bengio
- Yann LeCun
- Christian Szegedy
- Kaiming He
- Sergey Zagoruyko
- Ilya Sutskever
Who trusts Kry Yik-Chau Lui overall
Papers from Kry Yik-Chau Lui's perspective
Ordered by how strongly the researchers Kry Yik-Chau Lui 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
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- 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)
Their papers
- MMA Training: Direct Input Space Margin Maximization through Adversarial Training (2018) — 312 citations
- Improving GAN Training via Binarized Representation Entropy (BRE) Regularization (2018) — 19 citations
- On the Sensitivity of Adversarial Robustness to Input Data Distributions (2018) — 67 citations