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Leave Pima Indians alone: binary regression as a benchmark for Bayesian
  computation

Leave Pima Indians alone: binary regression as a benchmark for Bayesian computation

29 June 2015
Nicolas Chopin
James Ridgway
ArXiv (abs)PDFHTML

Papers citing "Leave Pima Indians alone: binary regression as a benchmark for Bayesian computation"

47 / 47 papers shown
Title
Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression
Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression
Filippo Ascolani
Giacomo Zanella
119
0
0
20 May 2025
Optimal lower bounds for logistic log-likelihoods
Optimal lower bounds for logistic log-likelihoods
Niccolò Anceschi
T. Rigon
Giacomo Zanella
Daniele Durante
58
1
0
14 Oct 2024
Grand Challenges in Bayesian Computation
Grand Challenges in Bayesian Computation
Anirban Bhattacharya
Antonio Linero
Chris. J. Oates
74
3
0
01 Oct 2024
Skew-symmetric approximations of posterior distributions
Skew-symmetric approximations of posterior distributions
Francesco Pozza
Daniele Durante
Botond Szabó
77
2
0
21 Sep 2024
Scalable expectation propagation for generalized linear models
Scalable expectation propagation for generalized linear models
Niccolò Anceschi
A. Fasano
Beatrice Franzolini
Giovanni Rebaudo
81
0
0
02 Jul 2024
Tuning diagonal scale matrices for HMC
Tuning diagonal scale matrices for HMC
Jimmy Huy Tran
T. S. Kleppe
72
4
0
12 Mar 2024
Expectation propagation for the smoothing distribution in dynamic probit
Expectation propagation for the smoothing distribution in dynamic probit
Niccolò Anceschi
A. Fasano
Giovanni Rebaudo
47
0
0
04 Sep 2023
Efficient computation of predictive probabilities in probit models via
  expectation propagation
Efficient computation of predictive probabilities in probit models via expectation propagation
A. Fasano
Niccolò Anceschi
Beatrice Franzolini
Giovanni Rebaudo
65
1
0
04 Sep 2023
Efficient expectation propagation for posterior approximation in
  high-dimensional probit models
Efficient expectation propagation for posterior approximation in high-dimensional probit models
A. Fasano
Niccolò Anceschi
Beatrice Franzolini
Giovanni Rebaudo
63
4
0
04 Sep 2023
Stein $Π$-Importance Sampling
Stein ΠΠΠ-Importance Sampling
Congye Wang
Ye Chen
Heishiro Kanagawa
Chris J. Oates
91
2
0
17 May 2023
Skewed Bernstein-von Mises theorem and skew-modal approximations
Skewed Bernstein-von Mises theorem and skew-modal approximations
Daniele Durante
Francesco Pozza
Botond Szabó
110
12
0
08 Jan 2023
Moment Propagation
Moment Propagation
J. Ormerod
Weichang Yu
81
0
0
21 Nov 2022
Higher-order stochastic integration through cubic stratification
Higher-order stochastic integration through cubic stratification
Nicolas Chopin
Mathieu Gerber
39
4
0
04 Oct 2022
An extension of the Unified Skew-Normal family of distributions and
  application to Bayesian binary regression
An extension of the Unified Skew-Normal family of distributions and application to Bayesian binary regression
P. Onorati
B. Liseo
67
3
0
07 Sep 2022
Bayesian conjugacy in probit, tobit, multinomial probit and extensions:
  A review and new results
Bayesian conjugacy in probit, tobit, multinomial probit and extensions: A review and new results
Niccolò Anceschi
A. Fasano
Daniele Durante
Giacomo Zanella
67
18
0
16 Jun 2022
Bounding Wasserstein distance with couplings
Bounding Wasserstein distance with couplings
N. Biswas
Lester W. Mackey
78
8
0
06 Dec 2021
Entropy-based adaptive Hamiltonian Monte Carlo
Entropy-based adaptive Hamiltonian Monte Carlo
Marcel Hirt
Michalis K. Titsias
P. Dellaportas
BDL
101
7
0
27 Oct 2021
Analytic natural gradient updates for Cholesky factor in Gaussian
  variational approximation
Analytic natural gradient updates for Cholesky factor in Gaussian variational approximation
Linda S. L. Tan
108
12
0
01 Sep 2021
JAGS, NIMBLE, Stan: a detailed comparison among Bayesian MCMC software
JAGS, NIMBLE, Stan: a detailed comparison among Bayesian MCMC software
Mario Beraha
Daniel Falco
A. Guglielmi
37
8
0
20 Jul 2021
Sticky PDMP samplers for sparse and local inference problems
Sticky PDMP samplers for sparse and local inference problems
J. Bierkens
Sebastiano Grazzi
Frank van der Meulen
Moritz Schauer
82
15
0
15 Mar 2021
A fresh take on 'Barker dynamics' for MCMC
A fresh take on 'Barker dynamics' for MCMC
Max Hird
Samuel Livingstone
Giacomo Zanella
93
9
0
17 Dec 2020
Ultimate Pólya Gamma Samplers -- Efficient MCMC for possibly
  imbalanced binary and categorical data
Ultimate Pólya Gamma Samplers -- Efficient MCMC for possibly imbalanced binary and categorical data
Gregor Zens
Sylvia Fruhwirth-Schnatter
Helga Wagner
SyDa
108
13
0
13 Nov 2020
Waste-free Sequential Monte Carlo
Waste-free Sequential Monte Carlo
Hai-Dang Dau
Nicolas Chopin
67
21
0
04 Nov 2020
Scalable computation of predictive probabilities in probit models with
  Gaussian process priors
Scalable computation of predictive probabilities in probit models with Gaussian process priors
JIAN-PENG Cao
Daniele Durante
M. Genton
61
11
0
03 Sep 2020
An invitation to sequential Monte Carlo samplers
An invitation to sequential Monte Carlo samplers
Chenguang Dai
J. Heng
Pierre E. Jacob
N. Whiteley
134
68
0
23 Jul 2020
A Class of Conjugate Priors for Multinomial Probit Models which Includes
  the Multivariate Normal One
A Class of Conjugate Priors for Multinomial Probit Models which Includes the Multivariate Normal One
A. Fasano
Daniele Durante
60
27
0
14 Jul 2020
Connecting the Dots: Numerical Randomized Hamiltonian Monte Carlo with
  State-Dependent Event Rates
Connecting the Dots: Numerical Randomized Hamiltonian Monte Carlo with State-Dependent Event Rates
T. S. Kleppe
54
12
0
04 May 2020
Semi-Exact Control Functionals From Sard's Method
Semi-Exact Control Functionals From Sard's Method
Leah F. South
Toni Karvonen
Christopher Nemeth
Mark Girolami
Chris J. Oates
93
17
0
31 Jan 2020
Scalable and Accurate Variational Bayes for High-Dimensional Binary
  Regression Models
Scalable and Accurate Variational Bayes for High-Dimensional Binary Regression Models
A. Fasano
Daniele Durante
Giacomo Zanella
69
31
0
15 Nov 2019
dynesty: A Dynamic Nested Sampling Package for Estimating Bayesian
  Posteriors and Evidences
dynesty: A Dynamic Nested Sampling Package for Estimating Bayesian Posteriors and Evidences
J. Speagle
88
1,221
0
03 Apr 2019
Online Sampling from Log-Concave Distributions
Online Sampling from Log-Concave Distributions
Holden Lee
Oren Mangoubi
Nisheeth K. Vishnoi
42
3
0
21 Feb 2019
Regularized Zero-Variance Control Variates
Regularized Zero-Variance Control Variates
Leah F. South
Chris J. Oates
Antonietta Mira
Christopher C. Drovandi
BDL
133
19
0
13 Nov 2018
Adaptive Tuning Of Hamiltonian Monte Carlo Within Sequential Monte Carlo
Adaptive Tuning Of Hamiltonian Monte Carlo Within Sequential Monte Carlo
Alexander K. Buchholz
Nicolas Chopin
Pierre E. Jacob
82
34
0
23 Aug 2018
Global consensus Monte Carlo
Global consensus Monte Carlo
Lewis J. Rendell
A. M. Johansen
Anthony Lee
N. Whiteley
91
40
0
24 Jul 2018
On a Metropolis-Hastings importance sampling estimator
On a Metropolis-Hastings importance sampling estimator
Daniel Rudolf
Björn Sprungk
77
21
0
18 May 2018
Unbiased and Consistent Nested Sampling via Sequential Monte Carlo
Unbiased and Consistent Nested Sampling via Sequential Monte Carlo
R. Salomone
Leah F. South
A. M. Johansen
Christopher C. Drovandi
Dirk P. Kroese
122
34
0
10 May 2018
Conjugate Bayes for probit regression via unified skew-normal
  distributions
Conjugate Bayes for probit regression via unified skew-normal distributions
Daniele Durante
84
58
0
26 Feb 2018
Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo
Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo
Oren Mangoubi
Nisheeth K. Vishnoi
155
53
0
24 Feb 2018
Controlled Sequential Monte Carlo
Controlled Sequential Monte Carlo
J. Heng
A. Bishop
George Deligiannidis
Arnaud Doucet
111
74
0
28 Aug 2017
Concentration of tempered posteriors and of their variational
  approximations
Concentration of tempered posteriors and of their variational approximations
Pierre Alquier
James Ridgway
117
126
0
28 Jun 2017
Discontinuous Hamiltonian Monte Carlo for discrete parameters and
  discontinuous likelihoods
Discontinuous Hamiltonian Monte Carlo for discrete parameters and discontinuous likelihoods
Akihiko Nishimura
David B. Dunson
Jianfeng Lu
42
2
0
23 May 2017
Bayesian Inference in the Presence of Intractable Normalizing Functions
Bayesian Inference in the Presence of Intractable Normalizing Functions
Jaewoo Park
M. Haran
TPM
155
73
0
23 Jan 2017
Quasi-stationary Monte Carlo and the ScaLE Algorithm
Quasi-stationary Monte Carlo and the ScaLE Algorithm
M. Pollock
Paul Fearnhead
A. M. Johansen
Gareth O. Roberts
98
18
0
12 Sep 2016
Stochastic Bouncy Particle Sampler
Stochastic Bouncy Particle Sampler
Ari Pakman
D. Gilboa
David Carlson
Liam Paninski
96
32
0
03 Sep 2016
GPU-accelerated Gibbs sampling: a case study of the Horseshoe Probit
  model
GPU-accelerated Gibbs sampling: a case study of the Horseshoe Probit model
Alexander Terenin
Shawfeng Dong
D. Draper
73
40
0
15 Aug 2016
High-dimensional Bayesian inference via the Unadjusted Langevin
  Algorithm
High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm
Alain Durmus
Eric Moulines
156
358
0
05 May 2016
Gibbs flow for approximate transport with applications to Bayesian
  computation
Gibbs flow for approximate transport with applications to Bayesian computation
J. Heng
Arnaud Doucet
Y. Pokern
OT
78
47
0
29 Sep 2015
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