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Good Initializations of Variational Bayes for Deep Models
v1v2 (latest)

Good Initializations of Variational Bayes for Deep Models

18 October 2018
Simone Rossi
Pietro Michiardi
Maurizio Filippone
    BDL
ArXiv (abs)PDFHTML

Papers citing "Good Initializations of Variational Bayes for Deep Models"

15 / 15 papers shown
Safety Monitoring of Machine Learning Perception Functions: a Survey
Safety Monitoring of Machine Learning Perception Functions: a SurveyInternational Conference on Climate Informatics (ICCI), 2024
Raul Sena Ferreira
Joris Guérin
Kevin Delmas
Jérémie Guiochet
H. Waeselynck
338
4
0
09 Dec 2024
SoftCVI: Contrastive variational inference with self-generated soft labels
SoftCVI: Contrastive variational inference with self-generated soft labels
Daniel Ward
Mark Beaumont
Matteo Fasiolo
BDL
629
1
0
22 Jul 2024
Evaluating Bayesian deep learning for radio galaxy classification
Evaluating Bayesian deep learning for radio galaxy classification
Devina Mohan
Anna M. M. Scaife
UQCVBDL
345
4
0
28 May 2024
On permutation symmetries in Bayesian neural network posteriors: a
  variational perspective
On permutation symmetries in Bayesian neural network posteriors: a variational perspectiveNeural Information Processing Systems (NeurIPS), 2023
Simone Rossi
Ankit Singh
T. Hannagan
231
3
0
16 Oct 2023
Quantifying Uncertainty in Deep Learning Classification with Noise in
  Discrete Inputs for Risk-Based Decision Making
Quantifying Uncertainty in Deep Learning Classification with Noise in Discrete Inputs for Risk-Based Decision Making
Maryam Kheirandish
Shengfan Zhang
D. Catanzaro
V. Crudu
UQCV
114
0
0
09 Oct 2023
Robust scalable initialization for Bayesian variational inference with
  multi-modal Laplace approximations
Robust scalable initialization for Bayesian variational inference with multi-modal Laplace approximationsProbabilistic Engineering Mechanics (PEM), 2023
Wyatt Bridgman
Reese E. Jones
Mohammad Khalil
176
3
0
12 Jul 2023
Variational Latent Branching Model for Off-Policy Evaluation
Variational Latent Branching Model for Off-Policy EvaluationInternational Conference on Learning Representations (ICLR), 2023
Qitong Gao
Ge Gao
Min Chi
Miroslav Pajic
OffRL
356
7
0
28 Jan 2023
Uncertainty Quantification for Deep Neural Networks: An Empirical
  Comparison and Usage Guidelines
Uncertainty Quantification for Deep Neural Networks: An Empirical Comparison and Usage GuidelinesSoftware testing, verification & reliability (STVR), 2022
Michael Weiss
Paolo Tonella
BDLUQCV
166
13
0
14 Dec 2022
Variational Inference for Additive Main and Multiplicative Interaction
  Effects Models
Variational Inference for Additive Main and Multiplicative Interaction Effects Models
A. A. L. D. Santos
R. Moral
Danilo A. Sarti
Andrew C. Parnell
105
2
0
29 Jun 2022
DeepBayes -- an estimator for parameter estimation in stochastic
  nonlinear dynamical models
DeepBayes -- an estimator for parameter estimation in stochastic nonlinear dynamical models
Anubhab Ghosh
M. Abdalmoaty
Saikat Chatterjee
H. Hjalmarsson
BDL
133
4
0
04 May 2022
Decision Theoretic Bootstrapping
Decision Theoretic BootstrappingInternational Journal for Uncertainty Quantification (IJUQ), 2021
P. Tavallali
Hamed Hamze Bajgiran
Danial Esaid
H. Owhadi
188
0
0
18 Mar 2021
All You Need is a Good Functional Prior for Bayesian Deep Learning
All You Need is a Good Functional Prior for Bayesian Deep LearningJournal of machine learning research (JMLR), 2020
Ba-Hien Tran
Simone Rossi
Dimitrios Milios
Maurizio Filippone
OODBDL
292
75
0
25 Nov 2020
Efficient Approximate Inference with Walsh-Hadamard Variational
  Inference
Efficient Approximate Inference with Walsh-Hadamard Variational Inference
Simone Rossi
Sébastien Marmin
Maurizio Filippone
BDL
158
1
0
29 Nov 2019
Walsh-Hadamard Variational Inference for Bayesian Deep Learning
Walsh-Hadamard Variational Inference for Bayesian Deep LearningNeural Information Processing Systems (NeurIPS), 2019
Simone Rossi
Sébastien Marmin
Maurizio Filippone
BDL
242
16
0
27 May 2019
Generalized Variational Inference: Three arguments for deriving new
  Posteriors
Generalized Variational Inference: Three arguments for deriving new Posteriors
Jeremias Knoblauch
Jack Jewson
Theodoros Damoulas
DRLBDL
480
114
0
03 Apr 2019
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