James Ridgway

Artificial Intelligence · 2015

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it; #20,613 of 35,345 by trust here, #31,361 by citations
• Statistics and Probability — 13 citations into it; #7,569 of 12,932 by trust here, #10,275 by citations
• Probabilistic & Bayesian Methods — 8 citations into it; #1,078 of 1,525 by trust here, #1,390 by citations
• Statistical Learning Theory — 6 citations into it

Whom James Ridgway trusts overall

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

1. David A. McAllester
2. Olivier Catoni
3. Radford M. Neal
4. David John Cameron MacKay
5. Gábor Lugosi
6. Alexandre B. Tsybakov
7. John Shawe-Taylor
8. Neil D. Lawrence
9. Enno Mammen
10. Peter J. Green

Who trusts James Ridgway overall

1. Pierre Alquier
2. Nicholas Syring
3. Pascal Germain

Papers from James Ridgway's perspective

Ordered by how strongly the researchers James Ridgway 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. Learning Multiple Layers of Features from Tiny Images
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Pattern Recognition and Machine Learning
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• On the properties of variational approximations of Gibbs posteriors (2015) — 286 citations