F. J. Breidt

Statistics and Probability · 2000–2017

A researcher in the Science corpus: 9 papers; trusts 34 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 59 citations into it; #2,248 of 12,932 by trust here, #4,517 by citations
• Artificial Intelligence — 22 citations into it; #15,691 of 35,345 by trust here, #33,294 by citations
• Management Science and Operations Research — 13 citations into it; #10,919 of 11,946 by trust here, #9,931 by citations
• Economics and Econometrics — 8 citations into it; #21,055 of 23,481 by trust here, #20,730 by citations
• Computational Mechanics — 5 citations into it
• Environmental Engineering — 5 citations into it; #1,904 of 5,479 by trust here, #4,694 by citations

Whom F. J. Breidt trusts overall

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

1. Matt P. Wand
2. William S. Cleveland
3. Jean D. Opsomer
4. David Ruppert
5. Alan Dorfman
6. Robert Tibshirani
7. S. Jammalamadaka
8. Radford M. Neal
9. Gerda Claeskens
10. David M. Blei

Who trusts F. J. Breidt overall

1. Jean D. Opsomer
2. Hervé Cardot
3. K. McConville
4. Hui Zheng
5. Roderick J. A. Little
6. Giorgio Eduardo Montanari
7. Ronald E. McRoberts
8. Etienne Josserand
9. Gretchen G. Moisen
10. Giovanna Ranalli

Papers from F. J. Breidt's perspective

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

1. Regression Shrinkage and Selection via the Lasso
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Estimating the Dimension of a Model
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Robust Locally Weighted Regression and Smoothing Scatterplots
10. Long Short-Term Memory

Their papers

• Laplace Variational Approximation for Semiparametric Regression in the Presence of Heteroskedastic Errors (2016) — 5 citations
• Local polynomial regresssion estimators in survey sampling (2000) — 273 citations
• Non‐parametric small area estimation using penalized spline regression (2008) — 199 citations
• Endogenous post-stratification in surveys: Classifying with a sample-fitted model (2008) — 69 citations
• Model-assisted estimation for complex surveys using penalised splines (2005) — 137 citations
• Nonparametric small area estimation using penalized spline regression (2005) — 76 citations
• The General Projected Normal Distribution of Arbitrary Dimension: Modeling and Bayesian Inference (2017) — 51 citations
• Model-Assisted Survey Regression Estimation with the Lasso (2017) — 78 citations
• Maximum likelihood estimation for all-pass time series models (2006) — 80 citations