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Variance reduction properties of the reparameterization trick

Variance reduction properties of the reparameterization trick

27 September 2018
Ming Xu
M. Quiroz
Robert Kohn
Scott A. Sisson
    AAML
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Papers citing "Variance reduction properties of the reparameterization trick"

14 / 14 papers shown
Title
Learning the Regularization Strength for Deep Fine-Tuning via a Data-Emphasized Variational Objective
Learning the Regularization Strength for Deep Fine-Tuning via a Data-Emphasized Variational Objective
Ethan Harvey
Mikhail Petrov
Michael C. Hughes
45
0
0
28 Jan 2025
Bayesian Experimental Design via Contrastive Diffusions
Bayesian Experimental Design via Contrastive Diffusions
Jacopo Iollo
Christophe Heinkelé
Pierre Alliez
Florence Forbes
35
0
0
15 Oct 2024
You Only Accept Samples Once: Fast, Self-Correcting Stochastic
  Variational Inference
You Only Accept Samples Once: Fast, Self-Correcting Stochastic Variational Inference
Dominic B. Dayta
TPM
BDL
35
0
0
05 Jun 2024
Demystifying SGD with Doubly Stochastic Gradients
Demystifying SGD with Doubly Stochastic Gradients
Kyurae Kim
Joohwan Ko
Yian Ma
Jacob R. Gardner
53
0
0
03 Jun 2024
Provably Scalable Black-Box Variational Inference with Structured
  Variational Families
Provably Scalable Black-Box Variational Inference with Structured Variational Families
Joohwan Ko
Kyurae Kim
W. Kim
Jacob R. Gardner
BDL
35
2
0
19 Jan 2024
Provable convergence guarantees for black-box variational inference
Provable convergence guarantees for black-box variational inference
Justin Domke
Guillaume Garrigos
Robert Mansel Gower
30
18
0
04 Jun 2023
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport
Vy Vo
Trung Le
L. Vuong
He Zhao
Edwin V. Bonilla
Dinh Q. Phung
OT
34
4
0
25 May 2023
Embedding Synthetic Off-Policy Experience for Autonomous Driving via
  Zero-Shot Curricula
Embedding Synthetic Off-Policy Experience for Autonomous Driving via Zero-Shot Curricula
Eli Bronstein
S. Srinivasan
Supratik Paul
Aman Sinha
Matthew O'Kelly
Payam Nikdel
Shimon Whiteson
OffRL
8
18
0
02 Dec 2022
Manifold Gaussian Variational Bayes on the Precision Matrix
Manifold Gaussian Variational Bayes on the Precision Matrix
M. Magris
M. Shabani
Alexandros Iosifidis
39
2
0
26 Oct 2022
Hierarchical Model-Based Imitation Learning for Planning in Autonomous
  Driving
Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving
Eli Bronstein
Mark Palatucci
Dominik Notz
Brandyn White
Alex Kuefler
...
Punit Shah
Evan Racah
Benjamin Frenkel
Shimon Whiteson
Drago Anguelov
50
58
0
18 Oct 2022
Global convergence of optimized adaptive importance samplers
Global convergence of optimized adaptive importance samplers
Ömer Deniz Akyildiz
34
7
0
02 Jan 2022
Imbalanced Continual Learning with Partitioning Reservoir Sampling
Imbalanced Continual Learning with Partitioning Reservoir Sampling
C. Kim
Jinseo Jeong
Gunhee Kim
CLL
32
101
0
08 Sep 2020
Monte Carlo Gradient Estimation in Machine Learning
Monte Carlo Gradient Estimation in Machine Learning
S. Mohamed
Mihaela Rosca
Michael Figurnov
A. Mnih
45
400
0
25 Jun 2019
Gaussian variational approximation for high-dimensional state space
  models
Gaussian variational approximation for high-dimensional state space models
M. Quiroz
David J. Nott
Robert Kohn
32
40
0
24 Jan 2018
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