Matthew Tan

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it
• Reinforcement Learning — 15 citations into it

Whom Matthew Tan trusts overall

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

1. Diederik P. Kingma
2. Sergey Levine
3. Karen Simonyan
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Alex Krizhevsky

Papers from Matthew Tan's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Making Sense of Vision and Touch: Learning Multimodal Representations for Contact-Rich Tasks (2019) — 283 citations