Linh Hoang Tran

Artificial Intelligence · 2020

A researcher in the Science corpus: 3 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 44 citations into it
• Optimization & Training — 11 citations into it

Whom Linh Hoang Tran trusts overall

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

1. Geoffrey E. Hinton
2. Andrey Malinin
3. Jimmy Ba
4. Yoshua Bengio
5. Diederik P. Kingma
6. Alex Krizhevsky
7. Christian Szegedy
8. Kaiming He
9. Yann LeCun
10. Radford M. Neal

Who trusts Linh Hoang Tran overall

1. Lin Wang
2. Kuk-Jin Yoon
3. Chaoyang He

Papers from Linh Hoang Tran's perspective

Ordered by how strongly the researchers Linh Hoang Tran 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• Hydra: Preserving Ensemble Diversity for Model Distillation (2020) — 65 citations
• Appendix for: How Good is the Bayes Posterior in Deep Neural Networks Really? (2020) — 424 citations
• The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks (2020) — 55 citations