Dinh Van Tran

Artificial Intelligence · 2018

A researcher in the Science corpus: 2 papers; trusts 30 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 37 citations into it
• Graph Learning — 33 citations into it
• Computer Vision and Pattern Recognition — 30 citations into it
• Molecular Biology — 9 citations into it
• Computational Chemistry & Drug Discovery — 8 citations into it
• Computational Theory and Mathematics — 8 citations into it
• Representation & Self-Supervised Learning — 7 citations into it

Whom Dinh Van Tran trusts overall

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

1. Alessio Micheli
2. Martin Simonovsky
3. S. V. N. Vishwanathan
4. Geoffrey E. Hinton
5. Marion Neumann
6. Karsten M. Borgwardt
7. James Atwood
8. Christian Szegedy
9. Nino Shervashidze
10. Nikil Wale

Who trusts Dinh Van Tran overall

1. Anton Tsitsulin

Papers from Dinh Van Tran's perspective

Ordered by how strongly the researchers Dinh Van Tran 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Going deeper with convolutions
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Pre-training Graph Neural Networks with Kernels (2018) — 30 citations
• On Filter Size in Graph Convolutional Networks (2018) — 53 citations