Nicholas Boyd

Artificial Intelligence · 2013

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 8 citations into it; #12,243 of 35,345 by trust here, #12,761 by citations
• Probabilistic & Bayesian Methods — 7 citations into it; #758 of 1,525 by trust here, #618 by citations

Whom Nicholas Boyd trusts overall

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

1. Tom Minka
2. Manfred Opper
3. David M. Blei
4. Matthew D. Hoffman
5. Antti Honkela
6. Michael I. Jordan
7. B. Recht

Who trusts Nicholas Boyd overall

1. Trevor Campbell
2. Thang D. Bui
3. Cuong V Nguyen
4. Yingzhen Li
5. Mikhail Yurochkin
6. Richard E. Turner
7. N. Foti
8. Matthew D. Hoffman
9. Chen Zeno
10. Linda S. L. Tan

Papers from Nicholas Boyd's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Expectation Propagation for approximate Bayesian inference
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Learning Multiple Layers of Features from Tiny Images
6. Latent Dirichlet Allocation
7. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
9. Long Short-Term Memory
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Streaming Variational Bayes (2013) — 368 citations