Thang Van Doan

Artificial Intelligence · 2018–2022

A researcher in the Science corpus: 5 papers; trusts 212 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 128 citations into it
• Computer Vision and Pattern Recognition — 105 citations into it
• Meta & Continual Learning — 50 citations into it; #836 of 1,041 by trust here, #742 by citations
• Generative Models — 39 citations into it
• Optimization & Training — 37 citations into it
• Reinforcement Learning — 25 citations into it
• Representation & Self-Supervised Learning — 19 citations into it
• Model Architectures — 13 citations into it

Whom Thang Van Doan trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Yann LeCun
5. Diederik P. Kingma
6. Ian J. Goodfellow
7. Marc'Aurelio Ranzato
8. Kaiming He
9. Ilya Sutskever
10. Alex Graves

Who trusts Thang Van Doan overall

1. Liyuan Wang
2. Ryo Karakida
3. Krishnan Raghavan
4. Xingxing Zhang
5. Liangzu Peng
6. Itay Evron
7. Timothée Lesort
8. Xinyuan Cao
9. Tero Karras
10. Seyed Iman Mirzadeh

Papers from Thang Van Doan's perspective

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

Their papers

• Online Adaptative Curriculum Learning for GANs (2018) — 43 citations
• A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix (2020) — 120 citations
• Building a Subspace of Policies for Scalable Continual Learning (2022) — 41 citations
• Efficient Continual Learning Ensembles in Neural Network Subspaces (2022) — 7 citations
• Multi-objective training of Generative Adversarial Networks with multiple discriminators (2019) — 72 citations