Matthew M. Graham

Artificial Intelligence · 2016

A researcher in the Science corpus: 1 paper; trusts 52 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it
• Probabilistic & Bayesian Methods — 23 citations into it
• Statistics and Probability — 21 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it
• Generative Models — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Matthew M. Graham trusts overall

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

1. Iain Murray
2. Max Welling
3. Edward Meeds
4. Radford M. Neal
5. MARK A. Beaumont
6. Simon N. Wood
7. James C. Spall
8. Taye Samuel Faniran
9. Diederik P. Kingma
10. Ryan P. Adams

Who trusts Matthew M. Graham overall

1. Kyle Cranmer
2. George Papamakarios

Papers from Matthew M. Graham's perspective

Ordered by how strongly the researchers Matthew M. Graham 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. Learning Multiple Layers of Features from Tiny Images
8. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Asymptotically exact inference in differentiable generative models (2016) — 38 citations