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Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing?

Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing?

Kyurae Kim
Yian Ma
Jacob R. Gardner
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Papers citing "Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing?"

6 / 6 papers shown
Title
On Divergence Measures for Training GFlowNets
On Divergence Measures for Training GFlowNets
Tiago da Silva
Eliezer de Souza da Silva
Diego Mesquita
BDL
36
1
0
12 Oct 2024
Efficient Mixture Learning in Black-Box Variational Inference
Efficient Mixture Learning in Black-Box Variational Inference
A. Hotti
Oskar Kviman
Ricky Molén
Victor Elvira
Jens Lagergren
49
1
0
11 Jun 2024
Understanding and mitigating difficulties in posterior predictive evaluation
Understanding and mitigating difficulties in posterior predictive evaluation
Abhinav Agrawal
Justin Domke
UQCV
47
0
0
30 May 2024
Kernel Semi-Implicit Variational Inference
Kernel Semi-Implicit Variational Inference
Ziheng Cheng
Longlin Yu
Tianyu Xie
Shiyue Zhang
Cheng Zhang
35
2
0
29 May 2024
On the Difficulty of Unbiased Alpha Divergence Minimization
On the Difficulty of Unbiased Alpha Divergence Minimization
Tomas Geffner
Justin Domke
62
18
0
19 Oct 2020
A Rule for Gradient Estimator Selection, with an Application to Variational Inference
A Rule for Gradient Estimator Selection, with an Application to Variational Inference
Tomas Geffner
Justin Domke
48
6
0
05 Nov 2019