Alexander Ropson

Probabilistic & Bayesian Methods · 2011

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 24 researchers here, as inferred from the citation graph.

Subfields

• Probabilistic & Bayesian Methods — 6 citations into it; #515 of 1,525 by trust here, #658 by citations
• Artificial Intelligence — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Alexander Ropson trusts overall

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

1. N. Schraudolph
2. Martin J. Wainwright
3. Joris M. Mooij
4. Kevin P. Murphy
5. Geoffrey E. Hinton

Who trusts Alexander Ropson overall

1. Yoshua Bengio
2. David Belanger
3. Ian J. Goodfellow
4. Aaron C. Courville
5. Li Deng
6. Yoon Kim
7. Philemon Brakel
8. John R. Hershey
9. Andrew McCallum
10. Veselin Stoyanov

Papers from Alexander Ropson's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. A Fast Learning Algorithm for Deep Belief Nets
3. Gradient-based learning applied to document recognition
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure (2011) — 132 citations