Taesung Lee

Artificial Intelligence · 2018

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it
• Safety, Robustness & Interpretability — 17 citations into it
• Computer Vision and Pattern Recognition — 13 citations into it
• Model Architectures — 6 citations into it

Whom Taesung Lee trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alex Krizhevsky
2. Diederik P. Kingma
3. Yann LeCun
4. François Chollet
5. Geoffrey E. Hinton
6. Nicolas Papernot
7. Yoshua Bengio
8. Adam Coates
9. Jimmy Ba
10. Dan Claudiu Ciresan

Who trusts Taesung Lee overall

1. Matthew Jagielski
2. Tribhuvanesh Orekondy
3. Nicholas Carlini
4. Bernt Schiele
5. Sebastian Szyller

Papers from Taesung Lee's perspective

Ordered by how strongly the researchers Taesung Lee trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Learning Multiple Layers of Features from Tiny Images
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering (2018) — 980 citations
• Defending Against Model Stealing Attacks Using Deceptive Perturbations (2018) — 47 citations