Adam M. Johansen

According to our database, Adam M. Johansen authored at least 20 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Error bounds for particle gradient descent, and extensions of the log-Sobolev and Talagrand inequalities.

Rocco Caprio, Juan Kuntz, Samuel Power, Adam M. Johansen

CoRR, 2024

2023

Cost free hyper-parameter selection/averaging for Bayesian inverse problems with vanilla and Rao-Blackwellized SMC samplers.

Alessandro Viani, Adam M. Johansen, Alberto Sorrentino

Stat. Comput., December, 2023

Divide-and-Conquer Fusion.

Ryan S. Y. Chan, Murray Pollock, Adam M. Johansen, Gareth O. Roberts

J. Mach. Learn. Res., 2023

Momentum Particle Maximum Likelihood.

Jen Ning Lim, Juan Kuntz, Samuel Power, Adam M. Johansen

CoRR, 2023

Particle algorithms for maximum likelihood training of latent variable models.

Juan Kuntz, Jen Ning Lim, Adam M. Johansen

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

The node-wise Pseudo-marginal method: model selection with spatial dependence on latent graphs.

Denishrouf Thesingarajah, Adam M. Johansen

Stat. Comput., 2022

Product-form estimators: exploiting independence to scale up Monte Carlo.

Juan Kuntz, Francesca R. Crucinio, Adam M. Johansen

Stat. Comput., 2022

Solving Fredholm Integral Equations of the First Kind via Wasserstein Gradient Flows.

Francesca R. Crucinio, Valentin De Bortoli, Arnaud Doucet, Adam M. Johansen

CoRR, 2022

Scalable particle-based alternatives to EM.

Juan Kuntz, Adam M. Johansen

CoRR, 2022

2021

A spatio-temporal model to reveal oscillator phenotypes in molecular clocks: Parameter estimation elucidates circadian gene transcription dynamics in single-cells.

Måns Unosson, Marco Brancaccio, Michael Hastings, Adam M. Johansen, Bärbel Finkenstädt

PLoS Comput. Biol., 2021

Global Consensus Monte Carlo.

Lewis J. Rendell, Adam M. Johansen, Anthony Lee, Nick Whiteley

J. Comput. Graph. Stat., 2021

2020

Generalized Bayesian Filtering via Sequential Monte Carlo.

Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen

CoRR, 2020

Generalised Bayesian Filtering via Sequential Monte Carlo.

Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2017

Bayesian model comparison with un-normalised likelihoods.

Richard G. Everitt, Adam M. Johansen, Ellen Rowing, Melina Evdemon-Hogan

Stat. Comput., 2017

2015

Convergence of the k-Means Minimization Problem using Γ-Convergence.

Matthew Thorpe, Florian Theil, Adam M. Johansen, Neil Cade

SIAM J. Appl. Math., 2015

2012

Bayesian model comparison via path-sampling sequential Monte Carlo.

Yan Zhou, Adam M. Johansen, John A. D. Aston

Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

2010

On solving integral equations using Markov chain Monte Carlo methods.

Arnaud Doucet, Adam M. Johansen, Vladislav Z. B. Tadic

Appl. Math. Comput., 2010

2008

Markov Chains.

Adam M. Johansen

Proceedings of the Wiley Encyclopedia of Computer Science and Engineering, 2008

Particle methods for maximum likelihood estimation in latent variable models.

Adam M. Johansen, Arnaud Doucet, Manuel Davy

Stat. Comput., 2008

2006

Maximum Likelihood Parameter Estimation for Latent Variable Models Using Sequential Monte Carlo.

Adam M. Johansen, Arnaud Doucet, Manuel Davy

Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006