Trung Le

Computer Vision and Pattern Recognition · 2017–2018

A researcher in the Science corpus: 4 papers; trusts 176 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 61 citations into it; #12,089 of 21,575 by trust here, #10,677 by citations
• Generative Models — 52 citations into it; #1,706 of 1,956 by trust here, #1,382 by citations
• Artificial Intelligence — 48 citations into it; #30,884 of 35,345 by trust here, #25,040 by citations
• Optimization & Training — 18 citations into it; #2,416 of 2,601 by trust here, #1,661 by citations
• Model Architectures — 11 citations into it
• Evaluation & Benchmarks — 9 citations into it
• Signal Processing — 8 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Trung Le trusts overall

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

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

Who trusts Trung Le overall

1. Ngoc-Trung Tran
2. Viet-Hung Tran
3. Mathijs Pieters
4. Gonçalo Mordido
5. Divya Saxena
6. Quan Hoang
7. Ngoc-Bao Nguyen
8. Yihan Cao
9. Steven C. H. Hoi
10. Garrett Wilson

Papers from Trung Le's perspective

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

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

Their papers

• Dual Discriminator Generative Adversarial Nets (2017) — 346 citations
• Multi-Generator Generative Adversarial Nets (2017) — 69 citations
• MGAN: Training Generative Adversarial Nets with Multiple Generators (2018) — 250 citations
• Large-scale Online Kernel Learning with Random Feature Reparameterization (2017) — 51 citations