Timothy Nguyen

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 3 papers; trusts 112 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 91 citations into it; #15,858 of 35,345 by trust here, #27,551 by citations
• Computer Vision and Pattern Recognition — 66 citations into it; #10,142 of 21,575 by trust here, #17,757 by citations
• Model Architectures — 22 citations into it
• Optimization & Training — 22 citations into it
• Scaling & Learning Theory — 22 citations into it
• Meta & Continual Learning — 19 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Statistical Learning Theory — 13 citations into it

Whom Timothy Nguyen trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Roman Novak
4. Yoshua Bengio
5. Diederik P. Kingma
6. Kaiming He
7. Jaehoon Lee
8. Yann LeCun
9. Lechao Xiao
10. Ilya Sutskever

Who trusts Timothy Nguyen overall

1. Bo Zhao
2. George Cazenavette
3. Hakan Bilen
4. Tongzhou Wang
5. Antonio Torralba
6. Roman Novak
7. Alexei A. Efros

Papers from Timothy Nguyen's perspective

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

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

Their papers

• Dataset Meta-Learning from Kernel Ridge-Regression (2020) — 326 citations
• Dataset Distillation with Infinitely Wide Convolutional Networks (2021) — 307 citations
• Architecture Matters in Continual Learning (2022) — 64 citations