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Deep Variational Bayes Filters: Unsupervised Learning of State Space
  Models from Raw Data

Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data

20 May 2016
Maximilian Karl
Maximilian Sölch
Justin Bayer
Patrick van der Smagt
    BDL
ArXivPDFHTML

Papers citing "Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data"

15 / 15 papers shown
Title
Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning under Partial Observability
Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning under Partial Observability
Carlos E. Luis
A. Bottero
Julia Vinogradska
Felix Berkenkamp
Jan Peters
142
1
0
20 Feb 2025
Meta-Dynamical State Space Models for Integrative Neural Data Analysis
Meta-Dynamical State Space Models for Integrative Neural Data Analysis
Ayesha Vermani
Josue Nassar
Hyungju Jeon
Matthew Dowling
Il Memming Park
104
1
0
07 Oct 2024
Deep Model-Based Reinforcement Learning for High-Dimensional Problems, a
  Survey
Deep Model-Based Reinforcement Learning for High-Dimensional Problems, a Survey
Aske Plaat
W. Kosters
Mike Preuss
BDL
OffRL
54
17
0
11 Aug 2020
Composing graphical models with neural networks for structured
  representations and fast inference
Composing graphical models with neural networks for structured representations and fast inference
Matthew J. Johnson
David Duvenaud
Alexander B. Wiltschko
S. R. Datta
Ryan P. Adams
BDL
OCL
64
483
0
20 Mar 2016
Deep Kalman Filters
Deep Kalman Filters
Rahul G. Krishnan
Uri Shalit
David Sontag
BDL
AI4TS
56
372
0
16 Nov 2015
A note on the evaluation of generative models
A note on the evaluation of generative models
Lucas Theis
Aaron van den Oord
Matthias Bethge
EGVM
74
1,142
0
05 Nov 2015
Embed to Control: A Locally Linear Latent Dynamics Model for Control
  from Raw Images
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images
Manuel Watter
Jost Tobias Springenberg
Joschka Boedecker
Martin Riedmiller
BDL
47
839
0
24 Jun 2015
A Recurrent Latent Variable Model for Sequential Data
A Recurrent Latent Variable Model for Sequential Data
Junyoung Chung
Kyle Kastner
Laurent Dinh
Kratarth Goel
Aaron Courville
Yoshua Bengio
DRL
BDL
64
1,250
0
07 Jun 2015
Variational Inference with Normalizing Flows
Variational Inference with Normalizing Flows
Danilo Jimenez Rezende
S. Mohamed
DRL
BDL
252
4,143
0
21 May 2015
Weight Uncertainty in Neural Networks
Weight Uncertainty in Neural Networks
Charles Blundell
Julien Cornebise
Koray Kavukcuoglu
Daan Wierstra
UQCV
BDL
114
1,878
0
20 May 2015
Learning Stochastic Recurrent Networks
Learning Stochastic Recurrent Networks
Justin Bayer
Christian Osendorfer
BDL
61
274
0
27 Nov 2014
Variational Tempering
Variational Tempering
Stephan Mandt
James McInerney
Farhan Abrol
Rajesh Ranganath
David M. Blei
BDL
46
55
0
07 Nov 2014
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
360
16,962
0
20 Dec 2013
Generating Sequences With Recurrent Neural Networks
Generating Sequences With Recurrent Neural Networks
Alex Graves
GAN
104
4,025
0
04 Aug 2013
Statistical inference for dynamical systems: a review
Statistical inference for dynamical systems: a review
K. Mcgoff
S. Mukherjee
Natesh S. Pillai
AI4CE
68
47
0
27 Apr 2012
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