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Markovian Score Climbing: Variational Inference with KL(p||q)

Markovian Score Climbing: Variational Inference with KL(p||q)

23 March 2020
C. A. Naesseth
Fredrik Lindsten
David M. Blei
ArXivPDFHTML

Papers citing "Markovian Score Climbing: Variational Inference with KL(p||q)"

14 / 14 papers shown
Title
Preference learning made easy: Everything should be understood through win rate
Preference learning made easy: Everything should be understood through win rate
Lily H. Zhang
Rajesh Ranganath
85
0
0
14 Feb 2025
Improving Tree Probability Estimation with Stochastic Optimization and
  Variance Reduction
Improving Tree Probability Estimation with Stochastic Optimization and Variance Reduction
Tianyu Xie
Musu Yuan
Minghua Deng
Cheng Zhang
24
0
0
09 Sep 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
51
0
0
22 Jul 2024
Torchtree: flexible phylogenetic model development and inference using
  PyTorch
Torchtree: flexible phylogenetic model development and inference using PyTorch
Mathieu Fourment
Matthew Macaulay
Christiaan J. Swanepoel
Xiang Ji
M. Suchard
Frederick A Matsen IV
BDL
29
0
0
26 Jun 2024
Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs
Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs
C. Margossian
Loucas Pillaud-Vivien
Lawrence K. Saul
UD
71
2
0
20 Mar 2024
Balanced Training of Energy-Based Models with Adaptive Flow Sampling
Balanced Training of Energy-Based Models with Adaptive Flow Sampling
Louis Grenioux
Eric Moulines
Marylou Gabrié
13
2
0
01 Jun 2023
State and parameter learning with PaRIS particle Gibbs
State and parameter learning with PaRIS particle Gibbs
Gabriel Victorino Cardoso
Yazid Janati
Sylvain Le Corff
Eric Moulines
Jimmy Olsson
25
6
0
02 Jan 2023
Markov Chain Score Ascent: A Unifying Framework of Variational Inference
  with Markovian Gradients
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients
Kyurae Kim
Jisu Oh
J. Gardner
Adji Bousso Dieng
Hongseok Kim
BDL
26
8
0
13 Jun 2022
Parallel Tempering With a Variational Reference
Parallel Tempering With a Variational Reference
Nikola Surjanovic
Saifuddin Syed
Alexandre Bouchard-Coté
Trevor Campbell
28
11
0
31 May 2022
Variational Inference with Locally Enhanced Bounds for Hierarchical
  Models
Variational Inference with Locally Enhanced Bounds for Hierarchical Models
Tomas Geffner
Justin Domke
18
5
0
08 Mar 2022
Empirical Evaluation of Biased Methods for Alpha Divergence Minimization
Empirical Evaluation of Biased Methods for Alpha Divergence Minimization
Tomas Geffner
Justin Domke
22
9
0
13 May 2021
Joint Stochastic Approximation and Its Application to Learning Discrete
  Latent Variable Models
Joint Stochastic Approximation and Its Application to Learning Discrete Latent Variable Models
Zhijian Ou
Yunfu Song
BDL
29
8
0
28 May 2020
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
323
4,203
0
23 Aug 2019
Variational Inference via $χ$-Upper Bound Minimization
Variational Inference via χχχ-Upper Bound Minimization
Adji Bousso Dieng
Dustin Tran
Rajesh Ranganath
John Paisley
David M. Blei
BDL
81
36
0
01 Nov 2016
1