Quang Pham

Artificial Intelligence · 2017–2022

A researcher in the Science corpus: 6 papers; trusts 706 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 184 citations into it; #20,129 of 35,345 by trust here, #15,542 by citations
• Computer Vision and Pattern Recognition — 143 citations into it; #13,323 of 21,575 by trust here, #15,529 by citations
• Representation & Self-Supervised Learning — 80 citations into it
• Meta & Continual Learning — 69 citations into it; #414 of 1,041 by trust here, #568 by citations
• Optimization & Training — 46 citations into it; #2,207 of 2,601 by trust here, #2,313 by citations
• Model Architectures — 27 citations into it
• Reinforcement Learning — 19 citations into it
• Signal Processing — 13 citations into it

Whom Quang Pham trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Kaiming He
5. Yoshua Bengio
6. Yann LeCun
7. Marc'Aurelio Ranzato
8. Jimmy Ba
9. Ilya Sutskever
10. Sergey Ioffe

Who trusts Quang Pham overall

1. Jorge Armando Mendez Mendez
2. Da-Wei Zhou
3. Zifeng Wang
4. Chenghao Liu
5. Eric Eaton
6. Liyuan Wang
7. Li Xu
8. Haiyan Yin
9. Zizhao Zhang
10. Steven C. H. Hoi

Papers from Quang Pham's perspective

Ordered by how strongly the researchers Quang Pham 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. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Online Deep Learning: Learning Deep Neural Networks on the Fly (2017) — 363 citations
• Continual Normalization: Rethinking Batch Normalization for Online Continual Learning (2022) — 76 citations
• Continual Learning, Fast and Slow (2021) — 57 citations
• Contextual Transformation Networks for Online Continual Learning (2021) — 61 citations
• DualNet: Continual Learning, Fast and Slow Supplementary Materials (2021)
• URLNet: Learning a URL Representation with Deep Learning for Malicious URL Detection (2018) — 325 citations