Thu Nguyen-Phuoc
Computer Vision and Pattern Recognition · with Richardt · 2019–2020
A researcher in the Science corpus: 2 papers; trusts 236 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 83 citations into it; #6,531 of 21,575 by trust here, #6,606 by citations
- Generative Models — 46 citations into it
- Computer Graphics and Computer-Aided Design — 25 citations into it; #440 of 1,584 by trust here, #329 by citations
- Artificial Intelligence — 20 citations into it
- Computational Mechanics — 17 citations into it; #5,474 of 10,001 by trust here, #2,112 by citations
- Optimization & Training — 6 citations into it
Whom Thu Nguyen-Phuoc trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Alex Krizhevsky
- Kaiming He
- Yoshua Bengio
- Yann LeCun
- Ilya Sutskever
- Christian Szegedy
- Jimmy Ba
- Karen Simonyan
Who trusts Thu Nguyen-Phuoc overall
- Michael Niemeyer
- Eric Chan
- Peng Wang
- Zhipeng Bao
- Jiatao Gu
- Lingjie Liu
- Zekun Hao
- Andreas Geiger
- Luke Melas-Kyriazi
- Anpei Chen
Papers from Thu Nguyen-Phuoc's perspective
Ordered by how strongly the researchers Thu Nguyen-Phuoc trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- HoloGAN: Unsupervised Learning of 3D Representations From Natural Images (2019) — 554 citations
- BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images (2020) — 253 citations