Cuong V Nguyen

Artificial Intelligence · 2017–2020

A researcher in the Science corpus: 7 papers; trusts 655 researchers and is trusted by 204 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 173 citations into it; #1,719 of 35,345 by trust here, #2,415 by citations
• Computer Vision and Pattern Recognition — 122 citations into it; #2,604 of 21,575 by trust here, #1,884 by citations
• Probabilistic & Bayesian Methods — 68 citations into it; #887 of 1,525 by trust here, #1,075 by citations
• Representation & Self-Supervised Learning — 66 citations into it; #260 of 3,145 by trust here, #380 by citations
• Optimization & Training — 38 citations into it; #2,048 of 2,601 by trust here, #1,216 by citations
• Model Architectures — 18 citations into it
• Reinforcement Learning — 18 citations into it
• Generative Models — 16 citations into it

Whom Cuong V Nguyen trusts overall

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

1. Diederik P. Kingma
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Kaiming He
5. Yoshua Bengio
6. Alex Graves
7. Yann LeCun
8. Radford M. Neal
9. Ross B. Girshick
10. L. Eon Bottou

Who trusts Cuong V Nguyen overall

1. Frederik Benzing
2. Fei Ye
3. Rahaf Aljundi
4. Arslan Chaudhry
5. Lucas Caccia
6. Jorge Armando Mendez Mendez
7. Sebastian Farquhar
8. Seyed Iman Mirzadeh
9. Siddharth Swaroop
10. Gido M. van de Ven

Papers from Cuong V Nguyen's perspective

Ordered by how strongly the researchers Cuong V 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. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Variational Continual Learning (2017) — 811 citations
• Improving and Understanding Variational Continual Learning (2019) — 53 citations
• Toward Understanding Catastrophic Forgetting in Continual Learning (2019) — 124 citations
• Streaming Sparse Gaussian Process Approximations (2017) — 125 citations
• LEEP: A New Measure to Evaluate Transferability of Learned Representations (2020) — 295 citations
• Transferability and Hardness of Supervised Classification Tasks (2019) — 209 citations
• Partitioned Variational Inference: A unified framework encompassing federated and continual learning (2018) — 58 citations