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ORCIDAdam M. Johansen
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2020 – today
- 2024
[c6]Jen Ning Lim, Juan Kuntz, Samuel Power, Adam M. Johansen:
Momentum Particle Maximum Likelihood. ICML 2024- [c5]Jen Ning Lim, Adam M. Johansen:
Particle Semi-Implicit Variational Inference. NeurIPS 2024 - [i9]Rocco Caprio, Juan Kuntz, Samuel Power, Adam M. Johansen:
Error bounds for particle gradient descent, and extensions of the log-Sobolev and Talagrand inequalities. CoRR abs/2403.02004 (2024) - [i8]Jen Ning Lim, Adam M. Johansen:
Particle Semi-Implicit Variational Inference. CoRR abs/2407.00649 (2024) - [i7]Rocco Caprio, Adam M. Johansen:
Fast convergence of the Expectation Maximization algorithm under a logarithmic Sobolev inequality. CoRR abs/2407.17949 (2024) - [i6]Francesca R. Crucinio, Adam M. Johansen:
Solving Fredholm Integral Equations of the Second Kind via Wasserstein Gradient Flows. CoRR abs/2409.19642 (2024) - [i5]Chatchuea Kimchaiwong, Jeremie Houssineau, Adam M. Johansen:
Redesigning the ensemble Kalman filter with a dedicated model of epistemic uncertainty. CoRR abs/2411.18864 (2024) - 2023
- [j10]Ryan S. Y. Chan, Murray Pollock, Adam M. Johansen, Gareth O. Roberts:
Divide-and-Conquer Fusion. J. Mach. Learn. Res. 24: 193:1-193:82 (2023) - [j9]Alessandro Viani
, Adam M. Johansen, Alberto Sorrentino:
Cost free hyper-parameter selection/averaging for Bayesian inverse problems with vanilla and Rao-Blackwellized SMC samplers. Stat. Comput. 33(6): 126 (2023) - [c4]Juan Kuntz, Jen Ning Lim, Adam M. Johansen:
Particle algorithms for maximum likelihood training of latent variable models. AISTATS 2023: 5134-5180 - [i4]Jen Ning Lim, Juan Kuntz, Samuel Power, Adam M. Johansen:
Momentum Particle Maximum Likelihood. CoRR abs/2312.07335 (2023) - 2022
- [j8]Juan Kuntz, Francesca R. Crucinio, Adam M. Johansen:
Product-form estimators: exploiting independence to scale up Monte Carlo. Stat. Comput. 32(1): 12 (2022) - [j7]Denishrouf Thesingarajah, Adam M. Johansen:
The node-wise Pseudo-marginal method: model selection with spatial dependence on latent graphs. Stat. Comput. 32(3): 43 (2022) - [i3]Juan Kuntz, Adam M. Johansen:
Scalable particle-based alternatives to EM. CoRR abs/2204.12965 (2022) - [i2]Francesca R. Crucinio, Valentin De Bortoli, Arnaud Doucet, Adam M. Johansen:
Solving Fredholm Integral Equations of the First Kind via Wasserstein Gradient Flows. CoRR abs/2209.09936 (2022) - 2021
- [j6]Lewis J. Rendell, Adam M. Johansen, Anthony Lee, Nick Whiteley:
Global Consensus Monte Carlo. J. Comput. Graph. Stat. 30(2): 249-259 (2021) - [j5]Måns Unosson, Marco Brancaccio, Michael Hastings, Adam M. Johansen, Bärbel Finkenstädt:
A spatio-temporal model to reveal oscillator phenotypes in molecular clocks: Parameter estimation elucidates circadian gene transcription dynamics in single-cells. PLoS Comput. Biol. 17(12) (2021) - 2020
- [c3]Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen:
Generalised Bayesian Filtering via Sequential Monte Carlo. NeurIPS 2020 - [i1]Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen:
Generalized Bayesian Filtering via Sequential Monte Carlo. CoRR abs/2002.09998 (2020)
2010 – 2019
- 2017
- [j4]Richard G. Everitt, Adam M. Johansen, Ellen Rowing, Melina Evdemon-Hogan:
Bayesian model comparison with un-normalised likelihoods. Stat. Comput. 27(2): 403-422 (2017) - 2015
- [j3]Matthew Thorpe, Florian Theil, Adam M. Johansen, Neil Cade:
Convergence of the k-Means Minimization Problem using Γ-Convergence. SIAM J. Appl. Math. 75(6): 2444-2474 (2015) - 2012
- [c2]Yan Zhou, Adam M. Johansen, John A. D. Aston:
Bayesian model comparison via path-sampling sequential Monte Carlo. SSP 2012: 245-248 - 2010
- [j2]Arnaud Doucet, Adam M. Johansen, Vladislav Z. B. Tadic:
On solving integral equations using Markov chain Monte Carlo methods. Appl. Math. Comput. 216(10): 2869-2880 (2010)
2000 – 2009
- 2008
- [j1]Adam M. Johansen, Arnaud Doucet, Manuel Davy:
Particle methods for maximum likelihood estimation in latent variable models. Stat. Comput. 18(1): 47-57 (2008) - [p1]Adam M. Johansen:
Markov Chains. Wiley Encyclopedia of Computer Science and Engineering 2008 - 2006
- [c1]Adam M. Johansen, Arnaud Doucet, Manuel Davy:
Maximum Likelihood Parameter Estimation for Latent Variable Models Using Sequential Monte Carlo. ICASSP (3) 2006: 640-643
Coauthor Index
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