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Efficient Gradient-Based Inference through Transformations between Bayes
  Nets and Neural Nets

Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets

3 February 2014
Diederik P. Kingma
Max Welling
    BDL
ArXivPDFHTML

Papers citing "Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets"

15 / 15 papers shown
Title
Meta-learning Amidst Heterogeneity and Ambiguity
Meta-learning Amidst Heterogeneity and Ambiguity
Kyeongryeol Go
Seyoung Yun
34
1
0
05 Jul 2021
Normalizing Flows for Probabilistic Modeling and Inference
Normalizing Flows for Probabilistic Modeling and Inference
George Papamakarios
Eric T. Nalisnick
Danilo Jimenez Rezende
S. Mohamed
Balaji Lakshminarayanan
TPM
AI4CE
62
1,631
0
05 Dec 2019
Semi-supervisedly Co-embedding Attributed Networks
Semi-supervisedly Co-embedding Attributed Networks
Zaiqiao Meng
Shangsong Liang
Jinyuan Fang
Teng Xiao
GNN
DRL
37
26
0
31 Oct 2019
Monte Carlo Gradient Estimation in Machine Learning
Monte Carlo Gradient Estimation in Machine Learning
S. Mohamed
Mihaela Rosca
Michael Figurnov
A. Mnih
45
397
0
25 Jun 2019
Compositional generalization through meta sequence-to-sequence learning
Compositional generalization through meta sequence-to-sequence learning
Brenden M. Lake
CoGe
32
196
0
12 Jun 2019
Stochastic Blockmodels meet Graph Neural Networks
Stochastic Blockmodels meet Graph Neural Networks
Nikhil Mehta
Lawrence Carin
Piyush Rai
BDL
35
80
0
14 May 2019
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward
  Energy-Based Model
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model
Erik Nijkamp
Mitch Hill
Song-Chun Zhu
Ying Nian Wu
29
209
0
22 Apr 2019
Dirichlet Variational Autoencoder
Dirichlet Variational Autoencoder
Weonyoung Joo
Wonsung Lee
Sungrae Park
Il-Chul Moon
BDL
DRL
27
101
0
09 Jan 2019
Sylvester Normalizing Flows for Variational Inference
Sylvester Normalizing Flows for Variational Inference
Rianne van den Berg
Leonard Hasenclever
Jakub M. Tomczak
Max Welling
BDL
DRL
18
249
0
15 Mar 2018
Generalization without systematicity: On the compositional skills of
  sequence-to-sequence recurrent networks
Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks
Brenden M. Lake
Marco Baroni
29
81
0
31 Oct 2017
Gradient Estimation Using Stochastic Computation Graphs
Gradient Estimation Using Stochastic Computation Graphs
John Schulman
N. Heess
T. Weber
Pieter Abbeel
OffRL
41
389
0
17 Jun 2015
Early Stopping is Nonparametric Variational Inference
Early Stopping is Nonparametric Variational Inference
D. Maclaurin
David Duvenaud
Ryan P. Adams
BDL
38
95
0
06 Apr 2015
How Auto-Encoders Could Provide Credit Assignment in Deep Networks via
  Target Propagation
How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation
Yoshua Bengio
47
181
0
29 Jul 2014
Reweighted Wake-Sleep
Reweighted Wake-Sleep
J. Bornschein
Yoshua Bengio
BDL
26
181
0
11 Jun 2014
Improving neural networks by preventing co-adaptation of feature
  detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
266
7,639
0
03 Jul 2012
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