David Buchman

Probabilistic & Bayesian Methods · 2011–2014

A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Probabilistic & Bayesian Methods — 19 citations into it
• Artificial Intelligence — 9 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it

Whom David Buchman trusts overall

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

1. Geoffrey E. Hinton
2. Marc'Aurelio Ranzato
3. Alex Krizhevsky
4. Yoshua Bengio
5. Yann LeCun
6. Pascal Vincent
7. Diederik P. Kingma
8. Aapo Hyvärinen
9. Radford M. Neal
10. Max Welling

Who trusts David Buchman overall

1. Yoshua Bengio
2. Majid Janzamin
3. Hanie Sedghi
4. Kyunghyun Cho

Papers from David Buchman's perspective

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

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

• Relational Logistic Regression: The Directed Analog of Markov Logic Networks (2014) — 29 citations
• On Autoencoders and Score Matching for Energy Based Models (2011) — 98 citations