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Stochastic Gradient MCMC Methods for Hidden Markov Models

Stochastic Gradient MCMC Methods for Hidden Markov Models

14 June 2017
Yian Ma
N. Foti
E. Fox
    BDL
ArXiv (abs)PDFHTML

Papers citing "Stochastic Gradient MCMC Methods for Hidden Markov Models"

15 / 15 papers shown
Title
Uncertainty-Informed Volume Visualization using Implicit Neural
  Representation
Uncertainty-Informed Volume Visualization using Implicit Neural Representation
Shanu Saklani
Chitwan Goel
Shrey Bansal
Zhe Wang
Soumya Dutta
Tushar M. Athawale
D. Pugmire
Christopher R. Johnson
94
0
0
12 Aug 2024
Uncertainty-Aware Deep Neural Representations for Visual Analysis of
  Vector Field Data
Uncertainty-Aware Deep Neural Representations for Visual Analysis of Vector Field Data
Atul Kumar
S. Garg
Soumya Dutta
82
0
0
23 Jul 2024
Visual Analysis of Prediction Uncertainty in Neural Networks for Deep
  Image Synthesis
Visual Analysis of Prediction Uncertainty in Neural Networks for Deep Image Synthesis
Soumya Dutta
Faheem Nizar
Ahmad Amaan
Ayan Acharya
AAML
89
1
0
22 May 2024
Stochastic Gradient MCMC for Massive Geostatistical Data
Stochastic Gradient MCMC for Massive Geostatistical Data
M. Abba
Brian J. Reich
Reetam Majumder
Brandon Feng
39
1
0
07 May 2024
Scalable Bayesian inference for the generalized linear mixed model
Scalable Bayesian inference for the generalized linear mixed model
S. Berchuck
Felipe A. Medeiros
Sayan Mukherjee
Andrea Agazzi
65
0
0
05 Mar 2024
Pigeonhole Stochastic Gradient Langevin Dynamics for Large Crossed Mixed
  Effects Models
Pigeonhole Stochastic Gradient Langevin Dynamics for Large Crossed Mixed Effects Models
Xinyu Zhang
Cheng Li
69
0
0
18 Dec 2022
Structured Stochastic Gradient MCMC
Structured Stochastic Gradient MCMC
Antonios Alexos
Alex Boyd
Stephan Mandt
BDL
73
13
0
19 Jul 2021
Quantifying Uncertainty in Deep Spatiotemporal Forecasting
Quantifying Uncertainty in Deep Spatiotemporal Forecasting
Dongxian Wu
Liyao (Mars) Gao
X. Xiong
Matteo Chinazzi
Alessandro Vespignani
Yi-An Ma
Rose Yu
AI4TS
89
71
0
25 May 2021
DenseHMM: Learning Hidden Markov Models by Learning Dense
  Representations
DenseHMM: Learning Hidden Markov Models by Learning Dense Representations
Joachim Sicking
Maximilian Pintz
Maram Akila
Tim Wirtz
60
1
0
17 Dec 2020
Challenges in Markov chain Monte Carlo for Bayesian neural networks
Challenges in Markov chain Monte Carlo for Bayesian neural networks
Theodore Papamarkou
Jacob D. Hinkle
M. T. Young
D. Womble
BDL
131
51
0
15 Oct 2019
Stochastic gradient Markov chain Monte Carlo
Stochastic gradient Markov chain Monte Carlo
Christopher Nemeth
Paul Fearnhead
BDL
81
139
0
16 Jul 2019
Stochastic Gradient MCMC for Nonlinear State Space Models
Stochastic Gradient MCMC for Nonlinear State Space Models
Christopher Aicher
Srshti Putcha
Christopher Nemeth
Paul Fearnhead
E. Fox
BDL
73
8
0
29 Jan 2019
Targeted stochastic gradient Markov chain Monte Carlo for hidden Markov
  models with rare latent states
Targeted stochastic gradient Markov chain Monte Carlo for hidden Markov models with rare latent states
Rihui Ou
Deborshee Sen
Alexander L. Young
David B. Dunson
BDL
26
0
0
31 Oct 2018
Stochastic Gradient MCMC for State Space Models
Stochastic Gradient MCMC for State Space Models
Christopher Aicher
Yian Ma
N. Foti
E. Fox
64
22
0
22 Oct 2018
Estimate exponential memory decay in Hidden Markov Model and its
  applications
Estimate exponential memory decay in Hidden Markov Model and its applications
F. Ye
Yian Ma
H. Qian
22
4
0
17 Oct 2017
1