Andrew Golightly

Artificial Intelligence · 2011–2018

A researcher in the Science corpus: 2 papers; trusts 12 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it; #31,052 of 35,345 by trust here, #30,347 by citations
• Probabilistic & Bayesian Methods — 13 citations into it; #1,411 of 1,525 by trust here, #1,365 by citations
• Statistics and Probability — 13 citations into it; #4,490 of 12,932 by trust here, #6,080 by citations
• Finance — 9 citations into it

Whom Andrew Golightly trusts overall

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

1. Diederik P. Kingma
2. Bjørn Eraker
3. Gareth O. Roberts
4. Danilo Jimenez Rezende
5. Darren J. Wilkinson
6. Yoshua Bengio
7. David M. Blei
8. Michalis K. Titsias
9. Geoffrey E. Hinton
10. Osnat Stramer

Who trusts Andrew Golightly overall

1. Vinayak A. Rao
2. Oksana A. Chkrebtii
3. Tom Ryder
4. Yee Whye Teh
5. Lawrence M. Murray
6. Debashish Chowdhury
7. Belinda Tzen
8. David Alexander Campbell
9. Hongqiao Wang
10. Fredrik Lindsten

Papers from Andrew Golightly's perspective

Ordered by how strongly the researchers Andrew Golightly 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. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
5. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Black-Box Variational Inference for Stochastic Differential Equations (2018) — 74 citations
• Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo (2011) — 314 citations