Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling

24 February 2016

Papers citing "Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling"

10 / 10 papers shown

Title
Semantic Probabilistic Control of Language Models Kareem Ahmed Catarina G Belém Padhraic Smyth Sameer Singh 44 0 0 04 May 2025
Massively Parallel Probabilistic Computing with Sparse Ising Machines Navid Anjum Aadit Andrea Grimaldi M. Carpentieri Luke Theogarajan J. Martinis G. Finocchio Kerem Y Çamsarı 58 141 0 06 Oct 2021
Regression from Dependent Observations C. Daskalakis Nishanth Dikkala Ioannis Panageas 19 30 0 08 May 2019
Distributed Metropolis Sampler with Optimal Parallelism Weiming Feng Thomas P. Hayes Yitong Yin 18 0 0 01 Apr 2019
HOGWILD!-Gibbs can be PanAccurate C. Daskalakis Nishanth Dikkala S. Jayanti 16 13 0 26 Nov 2018
Minibatch Gibbs Sampling on Large Graphical Models Christopher De Sa Vincent Chen W. Wong 26 19 0 15 Jun 2018
A Forest Mixture Bound for Block-Free Parallel Inference Neal Lawton Aram Galstyan Greg Ver Steeg 16 0 0 17 May 2018
Streaming Graph Challenge: Stochastic Block Partition E. Kao V. Gadepally M. Hurley Michael Jones J. Kepner ... Albert Reuther S. Samsi William S. Song Diane Staheli S. Smith 26 69 0 25 Aug 2017
Anytime Monte Carlo Lawrence M. Murray Sumeetpal S. Singh Anthony Lee 24 6 0 10 Dec 2016
DeepBach: a Steerable Model for Bach Chorales Generation Gaëtan Hadjeres F. Pachet Frank Nielsen 33 433 0 03 Dec 2016