Benjamin P. Fairfax

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All published works

Action	Title	Year	Authors
+ PDF Chat	Scalable multiple network inference with the joint graphical horseshoe	2024	Camilla Lingjærde Benjamin P. Fairfax Sylvia Richardson Hélène Ruffieux
+	Scalable Multiple Network Inference with the Joint Graphical Horseshoe	2022	Camilla Lingjærde Benjamin P. Fairfax Sylvia Richardson Hélène Ruffieux
+ PDF Chat	A global-local approach for detecting hotspots in multiple-response regression	2020	Hélène Ruffieux A. C. Davison Jörg Hager Jamie Inshaw Benjamin P. Fairfax Sylvia Richardson Leonardo Bottolo
+	A global-local approach for detecting hotspots in multiple-response regression	2018	Hélène Ruffieux A. C. Davison Jörg Hager Jamie Inshaw Benjamin P. Fairfax Sylvia Richardson Leonardo Bottolo
+	A global-local approach for detecting hotspots in multiple-response regression	2018	Hélène Ruffieux A. C. Davison Jörg Hager Jamie Inshaw Benjamin P. Fairfax Sylvia Richardson Leonardo Bottolo

Common Coauthors

Coauthor	Papers Together
Hélène Ruffieux	5
Sylvia Richardson	5
A. C. Davison	3
Leonardo Bottolo	3
Jörg Hager	3
Jamie Inshaw	2
Camilla Lingjærde	2
Jamie Inshaw	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Learning from a lot: Empirical Bayes for high‐dimensional model‐based prediction	2018	Mark A. van de Wiel Dennis E. te Beest Magnus Münch	3
+	The horseshoe estimator for sparse signals	2010	Carla M. Carvalho Nick Polson James G. Scott	3
+	EMVS: The EM Approach to Bayesian Variable Selection	2013	Veronika Ročková Edward I. George	3
+ PDF Chat	The horseshoe estimator: Posterior concentration around nearly black vectors	2014	Stéphanie van der Pas B. J. K. Kleijn Aad van der Vaart	3
+	Shrink Globally, Act Locally: Sparse Bayesian Regularization and Prediction*	2011	Nicholas G. Polson James G. Scott	3
+	Bayesian Multivariate Logistic Regression	2004	Sean M. O’Brien David B. Dunson	2
+	Bayesian Variable Selection in Linear Regression	1988	Toby J. Mitchell John J. Beauchamp	2
+	Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper)	2006	Andrew Gelman	2
+ PDF Chat	Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach	2014	Rémi Bardenet Arnaud Doucet Chris Holmes	2
+	Joint High‐Dimensional Bayesian Variable and Covariance Selection with an Application to eQTL Analysis	2013	Anindya Bhadra Bani K. Mallick	2
+ PDF Chat	Mean field variational Bayes for continuous sparse signal shrinkage: Pitfalls and remedies	2014	Sarah Elizabeth Neville John T. Ormerod M. P. Wand	2
+ PDF Chat	Scalable Variational Inference for Bayesian Variable Selection in Regression, and Its Accuracy in Genetic Association Studies	2012	Peter Carbonetto Matthew Stephens	2
+ PDF Chat	The Variable Selection Problem	2000	Edward I. George	2
+ PDF Chat	A sparse conditional Gaussian graphical model for analysis of genetical genomics data	2011	Jia‐Xin Yin Hongzhe Li	2
+ PDF Chat	Asymptotic Properties of Bayes Risk for the Horseshoe Prior	2013	Jyotishka Datta Jayanta K. Ghosh	2
+ PDF Chat	A Robust Generalized Bayes Estimator and Confidence Region for a Multivariate Normal Mean	1980	James O. Berger	2
+ PDF Chat	Proper Bayes Minimax Estimators of the Multivariate Normal Mean	1971	William E. Strawderman	2
+ PDF Chat	Nonparametric Bayesian density estimation on manifolds with applications to planar shapes	2010	Abhishek Bhattacharya David B. Dunson	2
+ PDF Chat	Variable selection using shrinkage priors	2016	Hanning Li Debdeep Pati	2
+	Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem	2010	James G. Scott James O. Berger	2
+	Bayesian Models for Sparse Regression Analysis of High Dimensional Data*	2011	Sylvia Richardson Leonardo Bottolo Jeffrey S. Rosenthal	2
+	Sparsity information and regularization in the horseshoe and other shrinkage priors	2017	Juho Piironen Aki Vehtari	2
+	Adaptive posterior contraction rates for the horseshoe	2017	Stéphanie van der Pas Botond Szabó Aad van der Vaart	2
+	Importance tempering	2008	Robert B. Gramacy Richard J. Samworth Ruth King	2
+	Asymptotic Properties of Bayes Risk of a General Class of Shrinkage Priors in Multiple Hypothesis Testing Under Sparsity	2015	Prasenjit Ghosh Xueying Tang Malay Ghosh Arijit Chakrabarti	2
+ PDF Chat	Default Bayesian analysis with global-local shrinkage priors	2016	Anindya Bhadra Jyotishka Datta Nicholas G. Polson Brandon T. Willard	2
+ PDF Chat	Bayesian Conditional Density Filtering	2018	Rajarshi Guhaniyogi Shaan Qamar David B. Dunson	2
+ PDF Chat	A global-local approach for detecting hotspots in multiple-response regression	2020	Hélène Ruffieux A. C. Davison Jörg Hager Jamie Inshaw Benjamin P. Fairfax Sylvia Richardson Leonardo Bottolo	2
+	Variational Tempering	2014	Stephan Mandt James O. McInerney Farhan Abrol Rajesh Ranganath David M. Blei	2
+	Conditions for posterior contraction in the sparse normal means problem	2016	Stéphanie van der Pas Jean-Bernard Salomond Johannes Schmidt-Hieber	2
+ PDF Chat	Efficient inference for genetic association studies with multiple outcomes	2017	Hélène Ruffieux A. C. Davison Jörg Hager Irina Irincheeva	2
+	The Spike-and-Slab LASSO	2016	Veronika Ročková Edward I. George	1
+ PDF Chat	Concentration of tempered posteriors and of their variational approximations	2020	Pierre Alquier James Ridgway	1
+ PDF Chat	Scaling It Up: Stochastic Search Structure Learning in Graphical Models	2015	Hao Wang	1
+	$α$-Variational Inference with Statistical Guarantees	2017	Yun Yang Debdeep Pati Anirban Bhattacharya	1
+ PDF Chat	Bayesian Graphical Lasso Models and Efficient Posterior Computation	2012	Hao Wang	1
+	On the properties of variational approximations of Gibbs posteriors	2015	Nicolás Chopin Pierre Alquier James Ridgway	1
+	Variational Inference: A Review for Statisticians	2017	David M. Blei Alp Kucukelbir Jon McAuliffe	1
+	The Horseshoe+ Estimator of Ultra-Sparse Signals	2016	Anindya Bhadra Jyotishka Datta Nicholas G. Polson Brandon T. Willard	1
+ PDF Chat	A weakly informative default prior distribution for logistic and other regression models	2008	Andrew Gelman Aleks Jakulin Maria Grazia Pittau Yu‐Sung Su	1
+	Advanced mean field methods: theory and practice	2001	Manfred Opper David Saad	1
+ PDF Chat	The Graphical Horseshoe Estimator for Inverse Covariance Matrices	2019	Yunfan Li Bruce Α. Craig Anindya Bhadra	1
+	Maximum Likelihood from Incomplete Data Via the <i>EM</i> Algorithm	1977	A. P. Dempster N. M. Laird Donald B. Rubin	1
+ PDF Chat	Tables for Computing Bivariate Normal Probabilities	1956	Donald B. Owen	1
+ PDF Chat	Optimal predictive model selection	2004	Maria Maddalena Barbieri James O. Berger	1
+ PDF Chat	Bayesian Inference of Multiple Gaussian Graphical Models	2014	Christine B. Peterson Francesco C. Stingo Marina Vannucci	1
+ PDF Chat	Matrix eQTL: ultra fast eQTL analysis via large matrix operations	2012	Andrey A. Shabalin	1
+ PDF Chat	Lasso Meets Horseshoe: A Survey	2019	Anindya Bhadra Jyotishka Datta Nicholas G. Polson Brandon T. Willard	1
+	Maximum likelihood estimation via the ECM algorithm: A general framework	1993	Xiao‐Li Meng Donald B. Rubin	1
+	Sparse inverse covariance estimation with the graphical lasso	2007	Jerome H. Friedman Trevor Hastie R. Tibshirani	1