#priors — Public Fediverse posts

'Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights', by Insung Kong, Yongdai Kim.

http://jmlr.org/papers/v26/24-0425.html

#priors #sparse #bnn

'Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights', by Insung Kong, Yongdai Kim.

http://jmlr.org/papers/v26/24-0425.html

#priors #sparse #bnn

'Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights', by Insung Kong, Yongdai Kim.

http://jmlr.org/papers/v26/24-0425.html

#priors #sparse #bnn

'Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights', by Insung Kong, Yongdai Kim.

http://jmlr.org/papers/v26/24-0425.html

#priors #sparse #bnn

'Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights', by Insung Kong, Yongdai Kim.

http://jmlr.org/papers/v26/24-0425.html

#priors #sparse #bnn

'Bayes Meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes', by Charles Riou, Pierre Alquier, Badr-Eddine Chérief-Abdellatif.

http://jmlr.org/papers/v26/23-025.html

#gibbs #priors #bernstein

'A Data-Adaptive RKHS Prior for Bayesian Learning of Kernels in Operators', by Neil K. Chada, Quanjun Lang, Fei Lu, Xiong Wang.

http://jmlr.org/papers/v25/22-1491.html

#priors #kernels #prior

'Evidence Estimation in Gaussian Graphical Models Using a Telescoping Block Decomposition of the Precision Matrix', by Anindya Bhadra, Ksheera Sagar, David Rowe, Sayantan Banerjee, Jyotishka Datta.

http://jmlr.org/papers/v25/23-0254.html

#priors #prior #gaussian

'Random measure priors in Bayesian recovery from sketches', by Mario Beraha, Stefano Favaro, Matteo Sesia.

http://jmlr.org/papers/v25/23-1058.html

#hashing #priors #prior

'Pre-trained Gaussian Processes for Bayesian Optimization', by Zi Wang et al.

http://jmlr.org/papers/v25/23-0269.html

#priors #prior #hyperparameters

'A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression', by Youngseok Kim, Wei Wang, Peter Carbonetto, Matthew Stephens.

http://jmlr.org/papers/v25/22-0953.html

#lasso #penalized #priors

'MAP- and MLE-Based Teaching', by Hans Ulrich Simon, Jan Arne Telle.

http://jmlr.org/papers/v25/23-1086.html

#likelihoods #priors #likelihood

Science Man, Priors, Psychbike, White Knuckle

Traxide, Sunday, 14 April (21:00)

https://montreal.askapunk.net/event/science-man-priors-psychbike-white-knuckle

Bar L'Esco 24th Anniversary w/ Priors + Whiteknuckle

L'Escogriffe Bar, Friday, 22 March (20:00)

https://montreal.askapunk.net/event/bar-lesco-24th-anniversary-with-priors-whiteknuckle

Chasing Better Deep Image Priors between Over- and Under-parameterization

Qiming Wu, Xiaohan Chen, Yifan Jiang, Zhangyang Wang

Action editor: Yanwei Fu.

https://openreview.net/forum?id=EwJJks2cSa

#priors #prior #deep

'Posterior Consistency for Bayesian Relevance Vector Machines', by Xiao Fang, Malay Ghosh.

http://jmlr.org/papers/v24/20-1012.html

#posterior #priors #relevance

'Posterior Consistency for Bayesian Relevance Vector Machines', by Xiao Fang, Malay Ghosh.

http://jmlr.org/papers/v24/20-1012.html

#posterior #priors #relevance

'Posterior Consistency for Bayesian Relevance Vector Machines', by Xiao Fang, Malay Ghosh.

http://jmlr.org/papers/v24/20-1012.html

#posterior #priors #relevance

'Posterior Consistency for Bayesian Relevance Vector Machines', by Xiao Fang, Malay Ghosh.

http://jmlr.org/papers/v24/20-1012.html

#posterior #priors #relevance

random walk, n., the route through an open plan office taken by a #statistician whilst waiting for their #MCMC chains to converge (hopefully). Expected length of route may depend on factors such as hardware specifications, informativeness of #priors, and whether there's a good coffee machine nearby. #statsodon #Bayesian #iamworking @pymc

'Prior Specification for Bayesian Matrix Factorization via Prior Predictive Matching', by Eliezer de Souza da Silva, Tomasz Kuśmierczyk, Marcelo Hartmann, Arto Klami.

http://jmlr.org/papers/v24/21-0623.html

#factorization #hyperparameters #priors

'Posterior Contraction for Deep Gaussian Process Priors', by Gianluca Finocchio, Johannes Schmidt-Hieber.

http://jmlr.org/papers/v24/21-0556.html

#priors #posterior #gaussian

'Posterior Contraction for Deep Gaussian Process Priors', by Gianluca Finocchio, Johannes Schmidt-Hieber.

http://jmlr.org/papers/v24/21-0556.html

#priors #posterior #gaussian

'Posterior Contraction for Deep Gaussian Process Priors', by Gianluca Finocchio, Johannes Schmidt-Hieber.

http://jmlr.org/papers/v24/21-0556.html

#priors #posterior #gaussian

'Posterior Contraction for Deep Gaussian Process Priors', by Gianluca Finocchio, Johannes Schmidt-Hieber.

http://jmlr.org/papers/v24/21-0556.html

#priors #posterior #gaussian

'Learning-augmented count-min sketches via Bayesian nonparametrics', by Emanuele Dolera, Stefano Favaro, Stefano Peluchetti.

http://jmlr.org/papers/v24/21-0096.html

#priors #nonparametrics #nonparametric