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. 1506.03101
  4. Cited By
Provable Bayesian Inference via Particle Mirror Descent

Provable Bayesian Inference via Particle Mirror Descent

9 June 2015
Bo Dai
Niao He
H. Dai
Le Song
ArXivPDFHTML

Papers citing "Provable Bayesian Inference via Particle Mirror Descent"

14 / 14 papers shown
Title
Hellinger-Kantorovich Gradient Flows: Global Exponential Decay of Entropy Functionals
Hellinger-Kantorovich Gradient Flows: Global Exponential Decay of Entropy Functionals
Alexander Mielke
Jia Jie Zhu
58
1
0
28 Jan 2025
DF2: Distribution-Free Decision-Focused Learning
DF2: Distribution-Free Decision-Focused Learning
Lingkai Kong
Wenhao Mu
Jiaming Cui
Yuchen Zhuang
B. Prakash
Bo Dai
Chao Zhang
OffRL
36
1
0
11 Aug 2023
Inferring Smooth Control: Monte Carlo Posterior Policy Iteration with
  Gaussian Processes
Inferring Smooth Control: Monte Carlo Posterior Policy Iteration with Gaussian Processes
Joe Watson
Jan Peters
21
15
0
07 Oct 2022
Adaptive Importance Sampling meets Mirror Descent: a Bias-variance
  tradeoff
Adaptive Importance Sampling meets Mirror Descent: a Bias-variance tradeoff
Anna Korba
Franccois Portier
14
12
0
29 Oct 2021
Federated Generalized Bayesian Learning via Distributed Stein
  Variational Gradient Descent
Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient Descent
Rahif Kassab
Osvaldo Simeone
FedML
15
45
0
11 Sep 2020
Implicit Generative Modeling for Efficient Exploration
Implicit Generative Modeling for Efficient Exploration
Neale Ratzlaff
Qinxun Bai
Fuxin Li
W. Xu
9
12
0
19 Nov 2019
Approximate Inference Turns Deep Networks into Gaussian Processes
Approximate Inference Turns Deep Networks into Gaussian Processes
Mohammad Emtiyaz Khan
Alexander Immer
Ehsan Abedi
M. Korzepa
UQCV
BDL
17
122
0
05 Jun 2019
A Spectral Approach to Gradient Estimation for Implicit Distributions
A Spectral Approach to Gradient Estimation for Implicit Distributions
Jiaxin Shi
Shengyang Sun
Jun Zhu
9
90
0
07 Jun 2018
A Unified Particle-Optimization Framework for Scalable Bayesian Sampling
A Unified Particle-Optimization Framework for Scalable Bayesian Sampling
Changyou Chen
Ruiyi Zhang
Wenlin Wang
Bai Li
Liqun Chen
13
86
0
29 May 2018
Stein Variational Gradient Descent as Gradient Flow
Stein Variational Gradient Descent as Gradient Flow
Qiang Liu
OT
28
270
0
25 Apr 2017
Stochastic Generative Hashing
Stochastic Generative Hashing
Bo Dai
Ruiqi Guo
Sanjiv Kumar
Niao He
Le Song
TPM
27
106
0
11 Jan 2017
Stein Variational Gradient Descent: A General Purpose Bayesian Inference
  Algorithm
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm
Qiang Liu
Dilin Wang
BDL
19
1,067
0
16 Aug 2016
Faster Stochastic Variational Inference using Proximal-Gradient Methods
  with General Divergence Functions
Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions
Mohammad Emtiyaz Khan
Reza Babanezhad
Wu Lin
Mark W. Schmidt
Masashi Sugiyama
28
49
0
31 Oct 2015
Bayesian Inference with Posterior Regularization and applications to
  Infinite Latent SVMs
Bayesian Inference with Posterior Regularization and applications to Infinite Latent SVMs
Jun Zhu
Ning Chen
Eric P. Xing
BDL
62
157
0
05 Oct 2012
1