Chris Fraley

Statistics and Probability · 2002–2012

A researcher in the Science corpus: 8 papers; trusts 52 researchers and is trusted by 119 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 52 citations into it; #461 of 12,932 by trust here, #689 by citations
• Artificial Intelligence — 34 citations into it; #1,911 of 35,345 by trust here, #4,101 by citations
• Molecular Biology — 14 citations into it; #8,659 of 17,773 by trust here, #15,850 by citations
• Probabilistic & Bayesian Methods — 11 citations into it
• Statistical Learning Theory — 10 citations into it
• Control and Systems Engineering — 9 citations into it
• Optimization & Training — 8 citations into it
• Atmospheric Science — 7 citations into it; #724 of 4,804 by trust here, #2,179 by citations

Whom Chris Fraley trusts overall

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

1. Adrian E. Raftery
2. Geoffrey J. McLachlan
3. P. Deb
4. Arthur P. Dempster
5. David Peel
6. Eric R. Ziegel
7. Padhraic Smyth
8. R. Fisher
9. Peter J. Green
10. Kenneth A. Bollen

Who trusts Chris Fraley overall

1. Adrian E. Raftery
2. Titus von der Malsburg
3. Luca Scrucca
4. Paul David McNicholas
5. Thomas Brendan Murphy
6. Bettina Grün
7. Nema Dean
8. Sara Dolnicar
9. Friedrich Leisch
10. Shravan Vasishth

Papers from Chris Fraley's perspective

Ordered by how strongly the researchers Chris Fraley 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. Long Short-Term Memory
6. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Model-Based Clustering, Discriminant Analysis, and Density Estimation (2002) — 4,492 citations
• Bayesian Regularization for Normal Mixture Estimation and Model-Based Clustering (2007) — 456 citations
• Least angle and ℓ1 penalized regression: A review (2008) — 310 citations
• Model-based Methods of Classification: Using the mclust Software in Chemometrics (2007) — 311 citations
• mclust Version 4 for R : Normal Mixture Modeling for Model-Based Clustering , Classification , and Density Estimation (2012) — 861 citations
• Probabilistic Quantitative Precipitation Forecasting Using Bayesian Model Averaging (2007) — 434 citations
• MCLUST Version 3 for R: Normal Mixture Modeling and Model-Based Clustering † (2007) — 491 citations
• Enhanced Model-Based Clustering, Density Estimation, and Discriminant Analysis Software: MCLUST (2003) — 325 citations