ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2103.01085
  4. Cited By
Challenges and Opportunities in High-dimensional Variational Inference
v1v2 (latest)

Challenges and Opportunities in High-dimensional Variational Inference

1 March 2021
Akash Kumar Dhaka
Alejandro Catalina
Manushi K. V. Welandawe
Michael Riis Andersen
Jonathan H. Huggins
Aki Vehtari
ArXiv (abs)PDFHTML

Papers citing "Challenges and Opportunities in High-dimensional Variational Inference"

13 / 13 papers shown
Title
FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering
FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering
Juehang Qin
Shixiao Liang
C. Tunnell
TPM
86
1
0
15 May 2025
Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix
Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix
C. Margossian
Lawrence K. Saul
94
2
0
14 Oct 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
233
1
0
22 Jul 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
158
2
0
20 Mar 2024
Rethinking Variational Inference for Probabilistic Programs with
  Stochastic Support
Rethinking Variational Inference for Probabilistic Programs with Stochastic Support
Tim Reichelt
C. Ong
Tom Rainforth
65
2
0
01 Nov 2023
Enhanced Sampling with Machine Learning: A Review
Enhanced Sampling with Machine Learning: A Review
S. Mehdi
Zachary Smith
Lukas Herron
Ziyue Zou
P. Tiwary
AI4CE
52
8
0
15 Jun 2023
On the Convergence of Black-Box Variational Inference
On the Convergence of Black-Box Variational Inference
Kyurae Kim
Jisu Oh
Kaiwen Wu
Yi-An Ma
Jacob R. Gardner
BDL
94
17
0
24 May 2023
Alpha-divergence Variational Inference Meets Importance Weighted
  Auto-Encoders: Methodology and Asymptotics
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics
Kamélia Daudel
Joe Benton
Yuyang Shi
Arnaud Doucet
DRL
76
11
0
12 Oct 2022
Gradients should stay on Path: Better Estimators of the Reverse- and
  Forward KL Divergence for Normalizing Flows
Gradients should stay on Path: Better Estimators of the Reverse- and Forward KL Divergence for Normalizing Flows
Lorenz Vaitl
K. Nicoli
Shinichi Nakajima
Pan Kessel
100
26
0
17 Jul 2022
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
Jacob R. Gardner
Adji Bousso Dieng
Hongseok Kim
BDL
89
8
0
13 Jun 2022
Pathfinder: Parallel quasi-Newton variational inference
Pathfinder: Parallel quasi-Newton variational inference
Lu Zhang
Bob Carpenter
A. Gelman
Aki Vehtari
134
41
0
09 Aug 2021
Mixture weights optimisation for Alpha-Divergence Variational Inference
Mixture weights optimisation for Alpha-Divergence Variational Inference
Kamélia Daudel
Randal Douc
84
9
0
09 Jun 2021
Pareto Smoothed Importance Sampling
Pareto Smoothed Importance Sampling
Aki Vehtari
Daniel Simpson
Andrew Gelman
Yuling Yao
Jonah Gabry
145
242
0
09 Jul 2015
1