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Dependent Multinomial Models Made Easy: Stick Breaking with the
  Pólya-Gamma Augmentation

Dependent Multinomial Models Made Easy: Stick Breaking with the Pólya-Gamma Augmentation

18 June 2015
Scott W. Linderman
Matthew J. Johnson
Ryan P. Adams
ArXivPDFHTML

Papers citing "Dependent Multinomial Models Made Easy: Stick Breaking with the Pólya-Gamma Augmentation"

14 / 14 papers shown
Title
Gradient-free variational learning with conditional mixture networks
Gradient-free variational learning with conditional mixture networks
Conor Heins
Hao Wu
Dimitrije Marković
Alexander Tschantz
Jeff Beck
Christopher L. Buckley
BDL
31
2
0
29 Aug 2024
On the Calibration and Uncertainty with Pólya-Gamma Augmentation for
  Dialog Retrieval Models
On the Calibration and Uncertainty with Pólya-Gamma Augmentation for Dialog Retrieval Models
Tong Ye
Shijing Si
Jianzong Wang
Ning Cheng
Zhitao Li
Jing Xiao
77
2
0
15 Mar 2023
Easy Variational Inference for Categorical Models via an Independent
  Binary Approximation
Easy Variational Inference for Categorical Models via an Independent Binary Approximation
M. Wojnowicz
Shuchin Aeron
Eric L. Miller
M. C. Hughes
25
2
0
31 May 2022
Personalized Federated Learning with Gaussian Processes
Personalized Federated Learning with Gaussian Processes
Idan Achituve
Aviv Shamsian
Aviv Navon
Gal Chechik
Ethan Fetaya
FedML
32
99
0
29 Jun 2021
Bayesian Classifier Fusion with an Explicit Model of Correlation
Bayesian Classifier Fusion with an Explicit Model of Correlation
Susanne Trick
Constantin Rothkopf
FedML
13
3
0
03 Jun 2021
Scalable Cross Validation Losses for Gaussian Process Models
Scalable Cross Validation Losses for Gaussian Process Models
M. Jankowiak
Geoff Pleiss
20
6
0
24 May 2021
Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma
  Augmented Gaussian Processes
Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes
Jake C. Snell
R. Zemel
33
63
0
20 Jul 2020
Fast Bayesian Estimation of Spatial Count Data Models
Fast Bayesian Estimation of Spatial Count Data Models
P. Bansal
Rico Krueger
D. Graham
21
8
0
07 Jul 2020
Learning Invariances using the Marginal Likelihood
Learning Invariances using the Marginal Likelihood
Mark van der Wilk
Matthias Bauer
S. T. John
J. Hensman
36
83
0
16 Aug 2018
PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits
PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits
Bianca Dumitrascu
Karen Feng
Barbara E. Engelhardt
13
40
0
18 May 2018
Reparameterizing the Birkhoff Polytope for Variational Permutation
  Inference
Reparameterizing the Birkhoff Polytope for Variational Permutation Inference
Scott W. Linderman
Gonzalo E. Mena
H. Cooper
Liam Paninski
John P. Cunningham
21
50
0
26 Oct 2017
Tractable Bayesian Density Regression via Logit Stick-Breaking Priors
Tractable Bayesian Density Regression via Logit Stick-Breaking Priors
T. Rigon
Daniele Durante
19
27
0
11 Jan 2017
Recurrent switching linear dynamical systems
Recurrent switching linear dynamical systems
Scott W. Linderman
Andrew C. Miller
Ryan P. Adams
David M. Blei
Liam Paninski
Matthew J. Johnson
36
69
0
26 Oct 2016
Ancestor Sampling for Particle Gibbs
Ancestor Sampling for Particle Gibbs
Fredrik Lindsten
Michael I. Jordan
Thomas B. Schon
57
61
0
25 Oct 2012
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