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Probabilistically-autoencoded horseshoe-disentangled multidomain
  item-response theory models

Probabilistically-autoencoded horseshoe-disentangled multidomain item-response theory models

5 December 2019
Joshua C. Chang
Shashaank Vattikuti
Carson C. Chow
ArXiv (abs)PDFHTML

Papers citing "Probabilistically-autoencoded horseshoe-disentangled multidomain item-response theory models"

14 / 14 papers shown
Title
Disentangling and Learning Robust Representations with Natural
  Clustering
Disentangling and Learning Robust Representations with Natural Clustering
Javier Antorán
A. Miguel
CoGeOODCMLDRL
65
19
0
27 Jan 2019
Structured Variational Learning of Bayesian Neural Networks with
  Horseshoe Priors
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors
S. Ghosh
Jiayu Yao
Finale Doshi-Velez
BDLUQCV
59
78
0
13 Jun 2018
Flipout: Efficient Pseudo-Independent Weight Perturbations on
  Mini-Batches
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches
Yeming Wen
Paul Vicol
Jimmy Ba
Dustin Tran
Roger C. Grosse
BDL
75
314
0
12 Mar 2018
Disentangled Sequential Autoencoder
Disentangled Sequential Autoencoder
Yingzhen Li
Stephan Mandt
CoGe
76
272
0
08 Mar 2018
Disentangling by Factorising
Disentangling by Factorising
Hyunjik Kim
A. Mnih
CoGeOOD
74
1,356
0
16 Feb 2018
TensorFlow Distributions
TensorFlow Distributions
Joshua V. Dillon
I. Langmore
Dustin Tran
E. Brevdo
Srinivas Vasudevan
David A. Moore
Brian Patton
Alexander A. Alemi
Matt Hoffman
Rif A. Saurous
GP
112
352
0
28 Nov 2017
Model Selection in Bayesian Neural Networks via Horseshoe Priors
Model Selection in Bayesian Neural Networks via Horseshoe Priors
S. Ghosh
Finale Doshi-Velez
BDL
82
120
0
29 May 2017
A simple sampler for the horseshoe estimator
A simple sampler for the horseshoe estimator
E. Makalic
Daniel F. Schmidt
84
238
0
17 Aug 2015
Practical Bayesian model evaluation using leave-one-out cross-validation
  and WAIC
Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC
Aki Vehtari
Andrew Gelman
Jonah Gabry
139
4,070
0
16 Jul 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCVBDL
905
9,364
0
06 Jun 2015
Weight Uncertainty in Neural Networks
Weight Uncertainty in Neural Networks
Charles Blundell
Julien Cornebise
Koray Kavukcuoglu
Daan Wierstra
UQCVBDL
194
1,894
0
20 May 2015
Comparison of Bayesian predictive methods for model selection
Comparison of Bayesian predictive methods for model selection
Juho Piironen
Aki Vehtari
101
279
0
30 Mar 2015
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
486
16,916
0
20 Dec 2013
Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable
  Information Criterion in Singular Learning Theory
Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory
Sumio Watanabe
156
2,395
0
14 Apr 2010
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