Matthew Johnson

Probabilistic & Bayesian Methods · with Hoffman · 2018

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

Subfields

• Probabilistic & Bayesian Methods — 20 citations into it

Whom Matthew Johnson trusts

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

1. Matthew D. Hoffman (in Probabilistic & Bayesian Methods)

Papers from Matthew Johnson's perspective

Ordered by how strongly the researchers Matthew Johnson 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. Long Short-Term Memory
3. GENERATIVE ADVERSARIAL NETS
4. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
5. Neural Turing Machines
6. Pixel Recurrent Neural Networks
7. AUTO-ENCODING VARIATIONAL BAYES
8. Neural Architecture Search with Reinforcement Learning
9. Image Transformer
10. Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Their papers

• Simple, Distributed, and Accelerated Probabilistic Programming (2018) — 61 citations