Matti Vihola

发表

Bayesian Inference of Non-Gaussian State Space Models [R package bssm version 1.0.1-1]

Jouni Helske, Matti Vihola, 2020 .

Establishing some order amongst exact approximations of MCMCs

Christophe Andrieu, Matti Vihola, C. Andrieu, 2014, 1404.6909.

Matti Vihola, M. Vihola, 2002 .

Quantitative Convergence Rates for Subgeometric Markov Chains

Gersende Fort, Christophe Andrieu, Matti Vihola, 2013, J. Appl. Probab..

Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo

Jouni Helske, Matti Vihola, Jordan Franks, 2016, Scandinavian Journal of Statistics.

Grapham: Graphical models with adaptive random walk Metropolis algorithms

Matti Vihola, M. Vihola, 2008, Comput. Stat. Data Anal..

Graphical model inference: Sequential Monte Carlo meets deterministic approximations

Fredrik Lindsten, Jouni Helske, Matti Vihola, 2019, NeurIPS.

Random set particle filter for bearings-only multitarget tracking

Matti Vihola, M. Vihola, 2005, SPIE Defense + Commercial Sensing.

Matti Vihola, Mikko Harju, Petri Salmela, 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Robust adaptive Metropolis algorithm with coerced acceptance rate

Matti Vihola, M. Vihola, 2010, Statistics and Computing.

Theoretical and Methodological Aspects of Markov Chain Monte Carlo Computations with Noisy Likelihoods

Christophe Andrieu, Matti Vihola, Anthony Lee, 2018, Handbook of Approximate Bayesian Computation.

Unbiased Estimators and Multilevel Monte Carlo

Matti Vihola, M. Vihola, 2015, Oper. Res..

Theoretical and methodological aspects of MCMC computations with noisy likelihoods

Christophe Andrieu, Matti Vihola, Anthony Lee, 2018 .

On the use of ABC-MCMC with inflated tolerance and post-correction

Matti Vihola, Jordan Franks, 2019 .

Conditional particle filters with diffuse initial distributions

Matti Vihola, Santeri Karppinen, M. Vihola, 2020, Statistics and Computing.

On the use of approximate Bayesian computation Markov chain Monte Carlo with inflated tolerance and post-correction

Matti Vihola, Jordan Franks, M. Vihola, 2019 .

Adaptive Metropolis algorithm using variational Bayesian adaptive Kalman filter

Simo Särkkä, Heikki Haario, Matti Vihola, 2013, Comput. Stat. Data Anal..

Ergonomic and Reliable Bayesian Inference with Adaptive Markov Chain Monte Carlo

Matti Vihola, M. Vihola, 2020 .

Conditional particle filters with diffuse initial distributions

Matti Vihola, Santeri Karppinen, 2021, Stat. Comput..

Hierarchical log Gaussian Cox process for regeneration in uneven-aged forests

Mikko Kuronen, Matti Vihola, Mari Myllymäki, 2021, Environmental and Ecological Statistics.

Unbiased Inference for Discretely Observed Hidden Markov Model Diffusions

Matti Vihola, Kody J. H. Law, Ajay Jasra, 2018, SIAM/ASA J. Uncertain. Quantification.

Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance

Matti Vihola, Jordan Franks, M. Vihola, 2017, 1706.09873.

Importance sampling and delayed acceptance via a Peskun type ordering

Matti Vihola, Jordan Franks, M. Vihola, 2017 .

Can the Adaptive Metropolis Algorithm Collapse Without the Covariance Lower Bound

Matti Vihola, M. Vihola, 2009, 0911.0522.

Coupled conditional backward sampling particle filter

Matti Vihola, Anthony Lee, Sumeetpal S. Singh, 2018, The Annals of Statistics.

On the stability and ergodicity of adaptive scaling Metropolis algorithms

Matti Vihola, M. Vihola, 2009, 0903.4061.

Conditional convex orders and measurable martingale couplings

Matti Vihola, Lasse Leskela, M. Vihola, 2014, 1404.0999.

Stochastic order characterization of uniform integrability and tightness

Matti Vihola, Lasse Leskela, M. Vihola, 2011 .

Uniform ergodicity of the iterated conditional SMC and geometric ergodicity of particle Gibbs samplers

Christophe Andrieu, Matti Vihola, Anthony Lee, 2013, 1312.6432.

Adaptive parallel tempering algorithm

Eric Moulines, Matti Vihola, Blazej Miasojedow, 2012, 1205.1076.