ResearchTrend.AI
Improving Gibbs Sampler Scan Quality with DoGS

Improving Gibbs Sampler Scan Quality with DoGS

Ioannis Mitliagkas
Lester W. Mackey
ArXiv (abs)PDFHTML

Papers citing "Improving Gibbs Sampler Scan Quality with DoGS"

5 / 5 papers shown
Title
Informed Correctors for Discrete Diffusion Models
Informed Correctors for Discrete Diffusion Models
Yixiu Zhao
Jiaxin Shi
F. Chen
Shaul Druckmann
Lester W. Mackey
Scott W. Linderman
133
15
0
30 Jul 2024
Dimension-Free Rates for Natural Policy Gradient in Multi-Agent Reinforcement Learning
Dimension-Free Rates for Natural Policy Gradient in Multi-Agent Reinforcement Learning
Carlo Alfano
Patrick Rebeschini
85
5
0
23 Sep 2021
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
Kartik Ahuja
Ethan Caballero
Dinghuai Zhang
Jean-Christophe Gagnon-Audet
Yoshua Bengio
Ioannis Mitliagkas
Irina Rish
OOD
73
270
0
11 Jun 2021
On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions
On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions
Kai Brügge
Asja Fischer
Christian Igel
34
0
0
26 Jun 2020
Optimal compromise between incompatible conditional probability distributions, with application to Objective Bayesian Kriging
Optimal compromise between incompatible conditional probability distributions, with application to Objective Bayesian Kriging
Joseph Muré
56
11
0
21 Mar 2017

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.