"Linear Convergence Bounds for Diffusion Models via Stochastic Localization'' (with J. Benton, V. De Bortoli & G. Deligiannidis), arXiv:2308.03686. Pdf
"Error Bounds for Flow Matching Methods" (with J. Benton & G. Deligiannidis). arXiv:2305.16860. Pdf
"Causal Falsification of Digital Twins" (with R Cornish, MF Taufiq & C Holmes). arXiv:2301.07210. Pdf
"Continuous diffusion for categorical data" (with S. Dieleman & et al.). arXiv:2211.15089. Pdf
"Spectral Diffusion Processes" (with A. Phillips, T. Seror, M. Hutchinson, V. De Bortoli & E. Mathieu). arXiv:2209.14125. Pdf
"Solving Fredholm Integral Equations of the First Kind via Wasserstein Gradient Flows" (with F. Crucinio, V. de Bortoli & A.M. Johansen). arXiv:2209.09936. Pdf
"A PAC-Bayes Bound for Deterministic Classifiers" (with E. Clerico, G. Deligiannidis & B. Guedj). arXiv:2209.02525. Pdf
"Ranking in Contextual Multi-Armed Bandits" (with A. Shidani & G. Deligiannidis). arXiv:2207.00109. Pdf
"Simulating Diffusion Bridges using Score Matching" (with V. De Bortoli, J. Thornton & J. Heng). arXiv:2111.07243. Pdf
"Metropolis--Hastings with Averaged Acceptance Ratios" (with C. Andrieu, S. Yildirim & N. Chopin). arXiv2101.01253. Pdf
"Noisy Adaptive Group Testing using Bayesian Sequential Experimental Design" (with M. Cuturi, O. Teboul, Q. Berthet & J.P. Vert). arXiv:2004.12508. Pdf
"Ensemble Rejection Sampling" (with G. Deligiannidis & S. Rubenthaler). arXiv:2001.09188. Pdf
"Schrödinger Bridge Samplers" (with E. Bernton, J. Heng & P.E. Jacob). arXiv:1912.13170. Pdf
"Mean-field Behaviour of Neural Tangent Kernel for Deep Neural Networks" (with S. Hayou & J. Rousseau). arXiv:1905.13654. Pdf (updated 03/10/19)
"Hamiltonian Descent Methods" (with C.J. Maddison, D. Paulin, Y.W. Teh & B. O'Donoghue). arXiv:1809.05042. Pdf
"Multivariate Stochastic Volatility with Co-Heteroscedasticity" (with J. Chan, R. Leon-Gonzalez & R.W. Strachan). GRIPS Discussion Papers 18-12. Pdf
"Scalable Monte Carlo Inference for State-Space Models" (with S. Yildirim & C. Andrieu). arXiv:1809.02527. Pdf
"Piecewise-Deterministic Markov Chain Monte Carlo" (with P. Vanetti, A. Bouchard-Côté & G. Deligiannidis). arXiv:1707.05296. (updated 15/05/18) Pdf
"On Embedded Hidden Markov Models and Particle Markov chain Monte Carlo Methods" (with A. Finke & A.M. Johansen). arXiv:1610.08962 Pdf
"Bayesian Nonparametric Image Segmentation using a Generalized Swedsen-Wang Algorithm" (with R. Xu & F. Caron), arXiv:1602:03048. Pdf
"Derivative-free Estimation of the Score Vector and Observed Information Matrix with Applications to State-Space Models'' (with P.E. Jacob & S. Rubenthaler), arXiv:1304:5768 (updated 07/2015).
"Perfect Simulation using Atomic Regeneration with Application to Sequential Monte Carlo" (with A. Lee and K. Łatuszyński), arXiv:1407.5770. Pdf
Edited book
A. Doucet, N. De Freitas & N.J. Gordon (editors), Sequential Monte Carlo Methods
in Practice, Springer-Verlag:
New York, 2001.
Publications
2023
"From Denoising Diffusions to Denoising Markov Models" (with J Benton, Y Shi, V De Bortoli & G Deligiannidis). Journal of the Royal Statistical Society Series B (with discussion), to appear. Pdf
"Quantitative Uniform Stability of the Iterative Proportional Fitting Procedure" (with G. Deligiannidis & V. De Bortoli). Annals of Applied Probability , 2023. Pdf
"Diffusion Schrödinger Bridges for Bayesian Computation" (with J. Heng & V. De Bortoli). Statistical Science, to appear 2023.
"Alpha-divergence Variational Inference Meets Importance Weighted Autoencoders: Methodology and Asymptotics" (with K. Daudel, J. Benton & Y. Shi). Journal of Machine Learning Research, 2023. Pdf
"Differentiable Samplers for Deep Latent Variable Models" (with E. Moulines & A. Thin). Philosophical Transactions of the Royal Society A, Theme issue on "Bayesian Inference: challenges, perspective, and prospects'', 2023.
"Trans-Dimensional Generative Modeling via Jump Diffusion Models" (with A. Campbell, W. Harvey, C. Weilbach, V. De Bortoli & T. Rainforth). NeurIPS, 2023 (spotlight). arXiv:2305.16261. Pdf
"Diffusion Schrödinger Bridge Matching" (with Y. Shi, V. De Bortoli & A. Campbell). arXiv:2303.16852. NeurIPS, 2023. Pdf
"A Unified Framework for U-Net Design and Analysis" (with C. Williams, F. Falck, G. Deligiannidis, C.C. Holmes & S. Syed). NeurIPS, 2023. arXiv:2305.19638. Pdf
"Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters" (with M. Noble, V. De Bortoli & A. Durmus). arXiv:2305.16557. NeurIPS, 2023 (spotlight). Pdf
"Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC" (with Y. Du, C. Durkan, R. Strudel, J.B, B Tenenbaum, S.Dieleman, R. Fergus, J. Sohl-Dickstein & W. Grathwohl). ICML, 2023. Pdf
"SE(3) Diffusion Model with Application to Protein Backbone Generation" (with J. Yim, B.L. Trippe, V. De Bortoli, E., R. Barzilay & T. Jaakkola). ICML, 2023. Pdf
"Denoising Diffusion Samplers" (with F. Vargas & W. Grathwohl). ICLR, 2023. Pdf
"Wide stochastic networks: Gaussian limit and PAC-Bayesian training" (with E. Clerico & G. Deligiannidis). Algorithmic Learning Theory, 2023. Pdf
"Categorical SDEs with Simplex Diffusion" (with P.H. Richemond & S. Dieleman). ICML Workshop on Sampling and Optimization in Discrete Space, 2023. Pdf
"Diffusion Generative Inverse Design" (with M. Vlastelica, T. Lopez-Guevara, K.R. Allen, P. Battaglia & K. Stachenfeld). ICML Workshop on Structured Probabilistic Inference and Generative Modeling, 2023. Pdf
2022
"Non-reversible Parallel Tempering: A Scalable Highly Parallel MCMC Scheme" (with S. Syed, A. Bouchard-Côté & G. Deligiannidis). Journal of the Royal Statistical Society Series B, vol. 84, no. 2, pp. 321--350, 2022. Pdf
"A Particle Method for Solving Fredholm Equations of the First Kind" (with F. Crucinio & A.M. Johansen). Journal of the American Statistical Association to appear arXiv:2009.09974. Pdf
"Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting" (with M. Vono & D. Paulin). Journal of Machine Learning Research, 2022. Pdf
"On Instrumental Variable Regression for Deep Offline Policy Evaluation" (with Y Chen, L Xu, C Gulcehre, TL Paine, A Gretton & N de Freitas). Journal of Machine Learning Research, vol. 23, pp. 1--69, 2022. Pdf
"COIN++: Data Agnostic Data Compression" (with E. Dupont, H. Loya, M. Alizadeh, A. Golinski & Y.W. Teh). Transactions on Machine Learning Research. Pdf
"Riemmanian Score-Based Generative Modeling" (with V. De Bortoli, E. Mathieu, M. Hutchinson, J. Thornton & Y.W. Teh). NeurIPS 2022 (Outstanding Paper Award - Oral). Pdf
"A Continuous Time Framework for Discrete Denoising Models" (with A. Campbell, J. Benton, V. de Bortoli, T. Rainforth & G. Deligiannidis). NeurIPS 2022 (Oral). Pdf
"A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs" (with F. Falck, C. Williams, D. Danks, G. Deligiannidis, C. Yau, C.C. Holmes & M. Willetts). NeurIPS 2022 (Oral).
"Score-Based Diffusion Meets Annealed Importance Sampling" (with W. Grathwohl, A.G.D.G. Matthews & H. Strathmann). NeurIPS 2022. Pdf
"Conformal Off-Policy Prediction in Contextual Bandits" (with M.F. Taufiq, J.F. Ton, R. Cornish & Y.W. Teh). NeurIPS 2022. Pdf
"Towards Learning Universal Hyperparameter Optimizers with Transformers" (with Y. Chen & al.). NeurIPS 2022. Pdf
"Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving" (with A. Singh, O. Makhlouf, M. Igl, J. Messias & Whiteson). CORL 2022. Pdf
"Conditional Simulation Using Diffusion Schrödinger Bridges" (with Y. Shi, V. De Bortoli & G. Deligiannidis). UAI 2022. Pdf
"Mitigating Statistical Bias within Differentially Private Synthetic Data" (with S. Ghalebikesabi, H. Wilde, J. Jewson, S. Vollmer & C.C. Holmes). UAI 2022 (oral). Pdf
"Chained Generalisation Bounds" (with E. Clerico, A. Shidani & G. Deligiannidis). COLT 2022. Pdf
"Continual Repeated Annealed Flow Transport Monte Carlo" (with A.G.D.G. Matthews, M. Arbel & D.J. Rezende). ICML 2022. Pdf
"Importance Weighting Approach in Kernel Bayes' Rule" (with L. Xu, Y. Chen & A. Gretton). ICML 2022. Pdf
"Learning Optimal Conformal Classifiers" (with D. Stutz, K. Dvijotham & A.T. Cemgil). ICLR 2022 (spotlight). Pdf
"Generative Models as Distributions of Functions" (with E. Dupont & Y.W. Teh). AISTATS 2022 (oral). Pdf
"Conditional Gaussian PAC-Bayes" (with E. Clerico & G. Deligiannidis). AISTATS 2022. Pdf
"On PAC-Bayesian Reconstruction Guarantees for VAEs" (with B-E Cherief-Abdelattif, Y. Shi & B. Guedj). AISTATS 2022. Pdf
2021
"Gibbs Flow for Approximate Transport with Applications to Bayesian Computation" (with J. Heng & Y. Pokern). Journal of the Royal Statistical Society Series B, vol. 83, no. 1, pp. 156--187, 2021. Pdf
"Randomized Hamiltonian Monte Carlo as Scaling Limit of the Bouncy Particle Sampler and Dimension-free Convergence Rates" (with G. Deligiannidis, D. Paulin & A. Bouchard-Côté). Annals of Applied Probability, vol. 31, no. 6, pp. 2612--2662, 2021. Pdf
"Large Sample Asymptotics of the Pseudo-Marginal Method" (with S. Schmon, G. Deligiannidis & M.K. Pitt). Biometrika, vol. 108, no. 1, pp. 37--51, 2021. Pdf
"Dual Space Preconditioning for Gradient Descent" (with C.J. Maddison, D. Paulin & Y.W. Teh). SIAM Journal on Optimization, vol. 31, no. 1, pp. 991--1016, 2021. Pdf
"Pseudo-marginal Hamiltonian Monte Carlo" (with J. Alenlov & F. Lindsten) . Journal of Machine Learning Research, vol. 22(141), pp. 1--45, 2021. Pdf
"Asymptotic Properties of Recursive Particle Maximum Likelihood Estimation" (with V.B. Tadic). IEEE Transactions on Information Theory, vol. 67, no. 3, pp. 1825--1848, 2021. Pdf
"Bias of Particle Approximations to Optimal Filter Derivative" (with V.B. Tadic). SIAM Journal on Control and Optimization, vol. 59, no. 1, pp. 727--748, 2021 . Pdf
"Network Consensus in the Wasserstein Metric Space of Probability Measures" (with A. Bishop). SIAM Journal on Control and Optimization, vol. 59, no. 5, pp. 3251--3277, 2021.Pdf
"Lithological Tomography with the Correlated Pseudo-Marginal Method" (with L. Freidli, N. Linde & D. Ginsbourger). Geophysical Journal International, to appear. Pdf
"Online Variational Filtering and Parameter Learning" (with A. Campbell, Y. Shi & T. Rainforth). NeurIPS 2021 (Oral). Pdf
"Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling" (with V. De Bortoli, J. Thornton & J. Heng). NeurIPS 2021 (Spotlight). Pdf
"NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform" (with A. Thin, Y. Janati El Idrissi, S. Le Corff, C. Ollion, E. Moulines, A. Durmus & C.P. Robert). NeurIPS 2021.Pdf
"Differentiable Particle Filtering via Entropy-Regularized Optimal Transport" (with A. Corenflos, J. Thornton & G. Deligiannidis). ICML 2021 (long oral). Pdf
"Annealed Flow Transport Monte Carlo" (with M. Arbel & A.G.D.G. Matthews). ICML 2021 (long oral). Pdf
"Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding" (with Y. Ruan, K. Ullrich, D. Severo, J. Townsend, A. Khisti, A. Makhzani & C.J. Maddison). ICML 2021 (long oral). Pdf
"Monte Carlo Variational Auto-Encoders" (with A. Thin, N. Kotelevskii, A. Durmus, M. Panov & E. Moulines). ICML 2021. Pdf
"Unbiased Gradient Estimation for Variational Auto-Encoders using Coupled Markov Chains" (with F.J. Ruiz, M.K. Titsias & T. Cemgil). UAI 2021. Pdf (Runner-up best paper award)
"Variational Inference with Continuously-Indexed Normalizing Flows" (with A. Caterini, R. Cornish & D. Sejdinovic). UAI 2021. Pdf
"Learning Deep Features in Instrumental Variable Regression" (with L. Xu, Y. Chen, S. Srinivasan, N. De Freitas & A. Gretton). ICLR 2021. Pdf
"Robust Pruning at Initialization" (with S. Hayou, J-F. Ton & Y.W. Teh). ICLR 2021. Pdf
"COIN: COmpression with Implicit Neural representations" (with E. Dupont, A. Golinski, M. Alizadeh & Y.W. Teh). ICLR Workshop on Neural Compression 2021. Pdf
"Stable Resnet" (with S. Hayou, E. Clerico, B. He, G. Deligiannidis & J. Rousseau). AISTATS 2021 (oral presentation). Pdf
2019-2020
"Controlled Sequential Monte Carlo" (with J. Heng, A. Bishop & G. Deligiannidis). Annals of Statistics, vol. 48, no. 5, pp. 2904--2929, 2020. PdfMatlab code
"Exponential Ergodicity of the Bouncy Particle Sampler" (with G. Deligiannidis & A. Bouchard-Côté). Annals of Statistics, vol. 47, no. 3, pp. 1268--1287, 2019. Pdf
"Analyticity of Entropy Rates of Continuous-state Hidden Markov Models" (with V.B. Tadic). IEEE Transactions on Information Theory, vol. 65, no. 12, pp. 7950--7975, 2019.Pdf
"Limit Theorems for Sequential MCMC Methods" (with A. Finke & A.M. Johansen). Advances in Applied Probability, vol. 52, pp. 377--403, 2020. Pdf
"Stability of Optimal Filter Higher-Order Derivatives" (with V.B. Tadic). Stochastic Processes and Their Applications, vol. 130, pp. 4808--4858, 2020. Pdf
"Unbiased MCMC for Intractable Target Distributions" (with L. Middleton, G. Deligiannidis & P.E. Jacob). Electronic Journal of Statistics, vol. 14, no. 2, pp. 2842--2891, 2020. Pdf
"Non-reversible Jump Algorithms for Bayesian Nested Model Selection" (with P. Gagnon). Journal of Computational and Graphical Statistics, vol. 30, no. 2, pp. 312--323, 2021. Pdf
"Modular Meta-Learning with Shrinkage" (with Y. Chen et al.), NeurIPS 2020 (spotlight). arXiv:1911.01340. Pdf
"Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows" (with R. Cornish, A. Caterini & G. Deligiannidis), ICML 2020. Pdf
"Unbiased Smoothing using Particle Independent Metropolis--Hastings" (with L. Middleton, G. Deligiannidis & P.E. Jacob), AISTATS, 2019. (oral) PdfCode
"Bernoulli Race Particle Filters" (with S. Schmon & G. Deligiannidis), AISTATS 2019. Pdf
"Scalable Metropolis--Hastings for Exact Bayesian Inference with Large Datasets" (with R. Cornish, P. Vanetti, A. Bouchard-Côté & G. Deligiannidis), ICML 2019. (oral) Pdf
"On the Impact of the Activation Function on Deep Neural Networks Training" (with S. Hayou & J. Rousseau), ICML 2019. Pdf
"Replica Conditional Sequential Monte Carlo" (with A. Shestopaloff), ICML 2019.
Discussion of Unbiased MCMC using Couplings by Jacob et al. (with P. Vanetti) , J. Roy. Stat. Soc. B, vol. 82, no. 3, pp. 592--593, 2020. Pdf
Discussion of Quasi-Stationary Monte Carlo and the Scale Algorithm by Pollock et al. (with P. Vanetti) , J. Roy. Stat. Soc. B, 2020. Pdf
2017-2018
"The Correlated Pseudo-Marginal Method" (with G. Deligiannidis & M.K. Pitt). Journal of the Royal Statistical Society Series B, vol. 80, no. 5, pp. 839--870, 2018. PdfCode
"The Bouncy Particle Sampler: A Non-Reversible Rejection Free Markov chain Monte Carlo Method" (with A. Bouchard-Côté & S.J. Vollmer).Journal of the American Statistical Association, vol. 113, pp. 855--867, 2018. PdfCodePiecewise deterministic MCMC library by T. Lienart. See also Msc Thesis by N. Galbraith Pdf with Python code
"Asymptotic Bias of Stochastic Gradient Search" (with V.B. Tadic). Annals of Applied Probability, vol. 27, no. 6, pp. 3255-3304, 2017 Pdf (extended version Pdf).
"On Markov chain Monte Carlo Methods for Tall Data'' (with R. Bardenet & C.C. Holmes). Journal of Machine Learning Research, vol. 18(47), pp. 1--43, 2017. PdfIPython notebook
"Particle Gibbs Split-Merge Sampling for Bayesian Inference in Mixture Models"
(with A. Bouchard-Côté & A. Roth). Journal of Machine Learning
Research, vol. 18(28), pp. 1--39, 2017. Pdf and code
"Generalized Pólya Urn for Time-Varying Pitman-Yor
Processes'' (with F. Caron et al.). Journal of Machine Learning
Research, vol. 18(27), pp. 1--32, 2017. PdfObject
tracking code
"Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains" (with J. Bierkens et al.). Statistics and Probability Letters, vol. 136, pp. 148-154, 2018 PdfCode.
"On Uncertainty Quantification in Hydrogeology and Hydrogeophysics" (with N. Linde, D. Ginsbourger, J. Irving & F. Nobile). Advances in Water Resources, vol. 110, pp. 166-181, 2017. Pdf
"Hamiltonian Variational Auto-Encoder" (with A. Caterini & D. Sejdinovic). NeurIPS 2018 Pdf
"Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling" (with A. Barbos, F. Caron & J-F. Giovannelli). NIPS 2017.
Pdf
"Particle Value Functions" (with C. Maddison et al.). Proc. Workshop ICLR, 2017. Pdf
"Sequential Monte Carlo Methods" (with A. Lee). in Handbook of Graphical Models (eds. Maathuis, Drton, Lauritzen & Wainwright), 2018 Pdf.
2015-2016
"Efficient Implementation of Markov chain Monte Carlo when Using an Unbiased Likelihood Estimator" (with M.K. Pitt, G. Deligiannidis & R. Kohn), Biometrika,
vol. 102, no. 2, pp. 295-313, 2015 (+18 pages Supplementary
material). Pdf
"Bayesian Phylogenetic Inference using a Combinatorial Sequential Monte Carlo Method" (with L. Wang & A. Bouchard-Côté).Journal of the American
Statistical Association, vol. 110, no. 512, pp. 1362-1374, 2015. PdfJava code
"On Particle Methods for Parameter Estimation in State-Space Models" (with N. Kantas et al.).Statistical Science, vol. 30, no. 3, pp. 328-351, 2015. Pdf
"Uniform
Stability of a Particle Approximation of the Optimal Filter Derivative"
(with P. Del Moral & S.S. Singh), SIAM J. Control Optimization,
vol. 53, no. 3, pp. 1278-1304, 2015. Pdf
"Particle Methods: An Introduction with Applications"
(with P. Del Moral), ESAIM: Proceedings,
vol. 44, pp. 1-46, 2014. Pdf
"Interacting Particle Markov chain Monte Carlo" (with T. Rainforth et al.), ICML 2016.
Code
2013-2014
"A
Lognormal Central Limit Theorem for Particle Approximations of
Normalizing Constants" (with J. Berard & P. Del Moral), Electronic J. Proba,
vol. 19, no. 94, pp. 1-28, 2014 Pdf.
"An Online Expectation-Maximization Algorithm for
Changepoint Models" (with S. Yildirim & S.S. Singh), J. Comp. Graph. Statist.,
vol. 22, no. 4, pp. 906-926, 2013. PdfMatlab
code
"Simulated Likelihood Inference for
Stochastic Volatility Models using Continuous Particle Filtering" (with
M.K. Pitt & S. Malik), Ann.
Inst. Stat. Math., vol 66, pp. 527-552,
2014. Pdf
"An Adaptive Interacting Wang-Landau Algorithm for
Automatic Density Exploration" (with L. Bornn, P. Jacob & P.
Del Moral), J. Comp.
Graph. Statist., vol. 22, no. 3, pp. 749-773,
2013. PdfR
package PAWL
"Fast Computation of Wasserstein Barycenters'' (with M.
Cuturi), ICML
2014. Pdf
"Towards Scaling Up MCMC for Large Datasets" (with R.
Bardenet & C.C. Holmes),
ICML 2014. PdfSupplementary
material
"Asynchronous Anytime Sequential Monte Carlo" (with B.
Paiges, F. Wood & Y.W. Teh), NIPS 2014 (oral).
2011-2012
"Particle Approximations of the Score and
Observed Information Matrix in State-Space Models with Application to
Parameter Estimation" (with G. Poyiadjis & S.S. Singh), Biometrika, vol.
98, no. 1, pp. 65-80, 2011. Pdf
"On the Conditional Distributions of Spatial Point
Processes" (with F. Caron, P. Del Moral & M. Pace), Advances in Applied
Probability, vol. 43, no. 2, pp. 301-307, 2011. Pdf
"An Adaptive
Sequential Monte Carlo
Method for Approximate Bayesian Computation" (with P. Del
Moral & A. Jasra), Statist.
Computing, vol. 22, no. 5, pp. 1009-1020, 2012. PdfC
code
"Bayesian Sparsity-Path-Analysis of Genetic Association
Signal using Generalized t Priors"
(with A. Lee, F. Caron & C.C. Holmes), Statistical Applications in
Genetics and Molecular Biology, vol. 11, no.
2, 2012.Pdf
"Efficient
Bayesian Inference for Generalized Bradley-Terry Models" (with F.
Caron), J.
Comp. Graph. Statist., vol. 21, no. 1, pp. 174-196, 2012. PdfWebpage
with Matlab code
"Particle Approximation of the Intensity Measures
of A Spatial Branching Point Process Arising in Multi-target Tracking"
(with F. Caron, P. Del Moral & M. Pace), SIAM J. Control Optimization,
vol. 49, no. 4, pp. 1766-1792, 2011. Pdf
"Fluctuations of Interacting Markov Chain Monte Carlo
Methods" (with B. Bercu & P. Del Moral), Stochastic Processes and Their
Applications, vol. 122, no. 4, pp. 1304-1331, 2012. Pdf
"Robust Inference
on Parameters via Particle Filters
and Sandwich Covariance Matrices" (with N.
Shephard), Technical report
Department of Economics, Oxford University, Discussion paper 606 Pdf.
"Efficient
Bayesian Inference for Multivariate Probit Models with Sparse
Inverse Correlation Matrices" (with A. Talhouk & K.P. Murphy), J. Comp. Graph. Statist.,
vol. 21, no. 3, pp. 739-757. PdfMatlab
code
"On Adaptive Resampling
Strategies for Sequential Monte Carlo
Methods"(with
P. Del Moral & A. Jasra), Bernoulli,
vol. 18, no. 1, pp. 252-278, 2012. Pdf
"On-line Changepoint Detection and Parameter Estimation
with Application to Genomic data" (with F. Caron & R.
Gottardo), Statist.
Computing, vol. 22, no. 2, pp. 579-595, 2012.
Pdf
"Exact approximation of Rao-Blackwellised particle filters"
(with A.M. Johansen & N. Whiteley), Proc. 16th IFAC SysId, 2012
Pdf
"On-line parameter estimation in general state-space models using a pseudo-likelihood approach"
(with C. Andrieu & V.B. Tadic), Proc. 16th IFAC SysId, 2012
Pdf
"Distributed
Maximum Likelihood for Simultaneous Self-Localization and Tracking in
Sensor Networks" (with N. Kantas & S.S. Singh), IEEE Trans. Signal Processing,
2012 Pdf
Discussion of Riemannian Manifold
Langevin and Hamiltonian Monte Carlo Methods by M. Girolami et al.
(with P. Jacob & A.M. Johansen), Journal
Royal Statistical Society B, 73(2):162, 2011.
"A Tutorial on Particle
Filtering and Smoothing: Fifteen years Later", (with A.M.
Johansen), in Handbook
of Nonlinear
Filtering (eds. D. Crisan et B. Rozovsky), Oxford
University
Press, 2011. Pdf
"On Nonlinear Markov chain Monte Carlo" (with C. Andrieu,
A. Jasra & P. Del Moral), Bernoulli,
vol. 17, no. 3, pp. 987-1014, 2011. Pdf
"Efficient
Bayesian Inference for
Switching State-Space Models using Discrete Particle Markov Chain
Monte Carlo methods" (with C. Andrieu & N.
Whiteley), Technical report no. 1004 Department of Mathematics Bristol
University Pdf
2009-2010
"Particle Markov chain Monte Carlo for Efficient Numerical
Simulation" (with C. Andrieu & R. Holenstein), in Monte Carlo and Quasi Monte
Carlo Methods 2008, Lecture Notes in Statistics, Springer,
pp. 45-60, 2009. Pdf
"Particle Markov chain Monte Carlo methods" (with C.
Andrieu & R. Holenstein) (with discussion), Journal Royal Statistical Society
B, vol. 72, no. 3, pp. 269-342, 2010. Pdf
"Forward
Smoothing using Sequential
Monte Carlo" (with P. Del Moral & S.S. Singh), Technical report Cambridge
University TR638, Sept. 2009, revised arXiv:1012:5390 Pdf
"On
the Utility of Graphics Cards to Perform Massively Parallel
Implementation of Advanced Monte Carlo Methods" (with A. Lee, C. Yau,
M. Giles & C.C. Holmes), J.
Comp. Graph. Statist., vol. 19, no. 4, pp. 769-789, 2010. PdfWebsite
with GPU code
"A Backward Particle Interpretation of Feynman-Kac
Formulae" (with P. Del Moral & S.S. Singh), ESAIM: Math. Model. Num. Analy.,
Special issue on Probabilistic Methods for PDEs, vol. 44, pp. 947-975,
2010. Pdf
"On Solving Integral Equations using Markov Chain Monte
Carlo Methods "
(with A. M. Johansen & V. B. Tadić), Applied Math. Computation, vol.
216, no. 10, pp. 2869-2880, 2010. Pdf
"A New Class of Interacting Markov chain Monte Carlo
Methods" (with P. Del Moral), Comptes
rendus Acad. Sci. Math., vol. 348, pp. 79-83, 2010.
"Interacting Markov chain Monte Carlo Methods for Solving
Nonlinear Measured-Valued Equations" (with P. Del Moral), Annals of Applied Probability, vol.
20, no. 2, pp. 593-639, 2010. Pdf
"Smoothing Algorithms for State-space Models" (with M.
Briers
&
S. Maskell), Annals
Institute Statistical Mathematics, vol. 62, no.
1, pp. 61-89, 2010. Pdf
"A
Boosting Approach to Structure Learning of High Dimensional Graphs with
and without Prior Knowledge" (S. Anjum & C.C. Holmes), Bioinformatics,
vol. 25, no. 22, pp. 2929-2936, 2009. Pdf
"An Efficient Computational
Approach to Prior
Sensitivity and Cross-Validation" (with L. Bornn & R.
Gottardo), Canadian
Journal of Statistics, vol. 38, no. 1, pp. 47-64,
2010. Pdf
"Sequentially Interacting Markov chain Monte Carlo" (with
A. Brockwell & P. Del Moral), Annals of Statistics,
vol. 38, no. 6, pp. 3387-3411, 2010. Pdf
"A
Functional Central Limit Theorem for a Class of Interacting Markov
Chain Monte Carlo Methods" (with B. Bercu & P. Del Moral), Electronic Journal of Probability, vol.
73, pp. 2130-2355, 2009. Pdf
Discussion
of Tracking of multiple merging and splitting targets: A statistical
perspective by Storlie et al. (with B. Vo), Statistica Sinica.
"A
Bayesian Approach to Joint Tracking and Identification of Geometric
Shapes in Video Sequences" (with P. Minvielle, A. Marrs & S.
Maskell), Image and
Vision Computing, vol. 28, pp. 111-123, 2010. Pdf
"An
Overview of
Sequential Monte Carlo Methods for Parameter Estimation in General
State-Space Models" (N. Kantas, S.S. Singh and J.M.
Maciejowski), Proceedings
IFAC System Identification (SySid)
Meeting, 2009.
"Bayesian Nonparametric Models on Decomposable Graphs"
(with F. Caron), NIPS 2009.
"An Expectation Maximization Algorithm for Continuous
Markov Decision Processes with Arbitrary Rewards" (with M. Hoffman, N.
De Freitas & J. Peters), AISTATS
2009. Pdf
"Particle
Markov Chain Monte
Carlo for Multiple Change-Point Problems" (with C. Andrieu
& N. Whiteley), Technical
report no. 0911 Department of
Mathematics Bristol University, 2009. Pdf
"A Hierarchical Bayesian Framework for Constructing Sparsity-inducing Priors" (with A. Lee, F. Caron & C.C. Holmes), 2009. Pdf
A Note on
Efficient Conditional Simulation of Gaussian Distributions Pdf
2007-2008
"Generalized Polya urn for
time-varying Dirichlet processes", (with F. Caron & M. Davy),
UAI 2007Pdf
"Sparse Bayesian Nonparametric Regression", (with F.
Caron), ICML
2008. Pdf
"Simulation-Based
Optimal Sensor
Scheduling with
Application to Observer Trajectory Planning", (with S.S. Singh et al.),
Automatica,
vol. 43, no.
5, pp. 817-830, 2007. Pdf
"A Note on Auxiliary Particle Filters", (with A.M.
Johansen), Statistics
and Probability Letters,
vol. 78, pp. 1498-1504, 2008. Pdf
"Particle methods for Maximum
Likelihood Parameter Estimation in Latent Variable Models",
(with A. M. Johansen & M. Davy), Statistics and Computing, vol.
18, pp. 47-57, 2008. Pdf
"A Note on the Convergence of the
Equi-Energy Sampler", (with C. Andrieu, A. Jasra & P. Del
Moral), Stochastic
Analysis and Applications, vol. 26, pp. 298-312, 2008. Pdf
"Sharp
Propagation of Chaos Estimates for Feynman-Kac Particle Models", (with
P. Del Moral & G.W. Peters), Teoriya
Veroyatnostei i ee Primeneniya,
vol. 51, no. 3, 2006. Reprinted in SIAM Theory
of Probability and Its Applications, vol. 51, no. 3, pp.
459-485, 2007 Pdf
"A Framework for Kernel-Based
Multi-Category
Classification", (with
S.I.
Hill), J. Artificial
Intell. Res., vol. 30, pp. 525-564, 2007. Pdf
"Bayesian policy
learning with trans-dimensional MCMC", (with M. Hoffman, N. De Freitas
& A. Jasra),
NIPS 2007. Pdf
"Efficient
Block Sampling Strategies for Sequential Monte Carlo", (with M. Briers
& S. Senecal), J.
Comp. Graph.
Statist., vol. 15, no. 3, pp. 693-711, 2006. Pdf
"Sequential Monte Carlo methods for
Bayesian Multi-target filtering with Random Finite Sets", (with B. Vo
& S.S. Singh), IEEE Trans.
Aerospace Elec. Systems, vol. 41, pp. 1224-1245,
2005. Pdf
"Sequential
Monte Carlo for Bayesian Computation" with discussion, (with P. Del
Moral & A. Jasra), Bayesian
Statistics 8, Oxford University Press, 2006. Pdf
preliminary version here
"Convergence
of the SMC Implementation of the PHD Filter", (with A. Johansen, S.S.
Singh & B. Vo), Methodology and Computing in Applied
Probability,
vol. 8, no. 2, pp. 265-291, 2006. Pdf
Discussion
of Exact and Computationally Efficient
Likelihood
Estimation of Discretely Observed Diffusions by Beskos et al. (with M.
Rousset) J.
Royal Statist. Soc. B, 2006. Pdf
"Exponential Forgetting and Geometric Ergodicity in General
State-Space Models", (with V.B. Tadic), Stochastic Processes and Their
Applications,
vol. 115, pp. 1408-1436, 2005. Pdf
"Fast Particle Smoothing: If I Had a Million
Particles", (with M. Klass et al.), ICML 2006 Pdf
"Space
Alternating Data Augmentation: Application to Finite Mixture of
Gaussians and Speaker Recognition" (with T. Matsui & S.
Senecal), Proc. IEEE
ICASSP, 2005. Pdf
"Towards practical N^2
Monte Carlo: The marginal particle filter", (with M. Klaas & N.
De
Freitas), UAI 2005 Pdf
"Online simulation-based
methods for parameter estimation in non linear non Gaussian state-space
models", (with C. Andrieu & V.B. Tadic), Proc. IEEE CDC
(invited paper), 2005 Pdf
"Particle methods for
optimal filter derivative: Application to parameter estimation", (with
G. Poyadjis & S.S. Singh), Proc.
IEEE ICASSP (invited paper), 2005 Pdf
Extended version of this paper Maximum Likelihood Parameter
Estimation using Particle Methods, Joint
Statistical Meeting, Pdf
"Sequential Monte Carlo
samplers for rare events", (with P. Del Moral & A.M. Johansen),
Proc.
6th International
Workshop on Rare Event Simulation, 2006 Pdf
"Sequential sampling for dynamic environment map
illumination", (with A.
Ghosh & W. Heidrich), Proc.
Eurographics
Symposium on
Rendering, 2006 Pdf
2003-2004
"Particle Motions in Absorbing Medium with Hard and Soft
Obstacles", (with
P. Del Moral), Stochastic Analysis and Applications,
vol. 22,
no. 5, pp. 1175-1207, 2004. Pdf
"Monte Carlo Smoothing for Nonlinear Time Series", (with
S.J.
Godsill
&
M. West), J. Amer. Stat. Assoc., vol. 99, no. 465,
pp. 156-168,
2004.
"Computational Methods for and from Bayesian Analysis",
(with C.
Andrieu
& C.P. Robert), Statistical Science, vol.
19, no. 1, 2004. Pdf
"Reversible Jump MCMC Strategies for Bayesian model
selection in
Autoregressive Processes", (with J. Vermaak,
C.
Andrieu
& S.J. Godsill), J. Time Series Analysis,
vol. 25, no. 6,
pp. 785-809, 2004. Pdf
Discussion on Efficient
Construction
of Reversible Jump MCMC Proposal Distributions by Brooks et al. (with
C. Andrieu) J.
Royal Statist. Soc. B, 2003.
"On a Class of Genealogical and Interacting Metropolis
Models"
(with P.
Del Moral). Seminaire de Proba. XXXVII, Ed. J.
Azema, M. Emery, M. Ledoux & M. Yor, Lecture Notes in
Mathematics,
Springer-Verlag Berlin, 2003. Pdf
"Efficient Particle Filtering for Jump Markov Systems -
Applications to
Time-Varying Autoregressions", (with C. Andrieu & M.
Davy), IEEE
Trans. Signal Processing, vol. 51, no. 7, pp. 1762-1770, 2003
Pdf
"An Introduction to MCMC for Machine Learning", (with C.
Andrieu,
N. de
Freitas & M.I. Jordan), Machine Learning,
vol. 50, pp.
5-43,
2003, Pdf
"Parameter Estimation in General State-Space Models using
Particle
Methods"
(with V.B. Tadic), Ann. Inst. Stat. Math., vol. 55,
no. 2, pp.
409-422,
2003. Read Biometrika
2010 Pdf
instead.
"Maintining Multimodality
through
Mixture
Tracking", (with J. Vermaak & P. Perez), ICCV 2003Download
it here
2001-2002
"Particle Filtering for Partially Observed Gaussian State
Space
Models",
(with C. Andrieu), J. Royal Statist. Soc. B,
vol.
64, no.4, pp. 827-836, 2002. Pdf
"Particle Filters for State Estimation of Jump Markov
Linear
Systems"
(with
N.J. Gordon and V. Krishnamurthy), IEEE Trans. Signal
Processing,
vol. 49, no.3, pp. 613-624, 2001. Pdf
"Convergence of Simulated Annealing using Foster-Lyapunov
Criteria",
(with
C. Andrieu & L. Breyer), J. Applied Probability,
vol.
38,
no. 4, pp. 975-994, 2001. Pdf
"Robust Full Bayesian Learning for Radial Basis Networks"
(with
C.
Andrieu
and J.F.G. de Freitas), Neural Computation, vol.
13, pp.
2359-2407,
2001. Pdf
"Marginal Maximum A Posteriori Estimation using MCMC" (with
S.J.
Godsill
& C.P. Robert), Statistics and Computing,
vol. 12, pp.
77-84,
2002. Pdf
"A Survey of Convergence Results on Particle Filtering for
Practitioners",
(with D. Crisan), IEEE Trans. Signal Processing,
vol. 50, no.
3,
pp. 736-746, 2002. Pdf
"Bayesian Curve Fitting with Applications to Signal
Segmentation",
(with
E. Punskaya, C. Andrieu & W.J. Fitzgerald), IEEE
Trans. Signal
Processing,
vol. 50, no. 3, pp. 747-758, 2002. Pdf
"Maximum a Posteriori Sequence Estimation via Monte Carlo
Particle Methods" (with S.J. Godsill & M. West), Ann. Inst. Stat. Math.
vol. 53, no.
1, pp. 82-96, 2001.
"Optimal Estimation and Cramer-Rao Bounds for
Partial
Non-Gaussian
State-Space Models" (with N. Bergman & N.J. Gordon), Ann.
Inst.
Stat. Math., vol. 52, no. 1, pp. 97-112, 2001. Pdf
"Iterative Algorithms for State Estimation of Jump Markov
Linear
Systems"
(with C. Andrieu), IEEE Trans. Signal Processing,
vol. 49, no.
6,
pp. 1216-1227, 2001. Pdf
"Bayesian Deconvolution of Noisy Filtered Point Processes"
(with
C.
Andrieu
& E. Barat), IEEE Trans. Signal Processing,
vol. 49, no. 1,
pp. 134-146, 2001. Pdf
" Rao-Blackwellised
Particle Filtering via Data Augmentation", (with C. Andrieu &
N. de Freitas), NIPS 2001. Pdf
"An Introduction to Sequential Monte Carlo Methods" (with
J.F.G.
de
Freitas
& N.J. Gordon) in Sequential Monte Carlo Methods in
Practice, New
York: Springer-Verlag, January 2001. Pdf
"Sequential Monte Carlo Methods for Optimal Filtering"
(with C.
Andrieu
& E. Punskaya) in Sequential Monte Carlo
Methods in
Practice, New
York: Springer-Verlag, January 2001.
"Sparse Bayesian Learning
for
Regression
and Classification using MCMC", (with S.S. Tham & R. Kitagari),
ICML 2002.
"Particle methods for Bayesian modeling and enhancement of
speech
signals",
(with J. Vermaak, C. Andrieu & S.J. Godsill), IEEE
Trans. Speech
and Audio Proc., vol. 10, no. 3, pp. 173-185, 2002.Pdf
1995-2000
"On Sequential Monte Carlo Sampling Methods for Bayesian
Filtering"
(with
S.J. Godsill & C. Andrieu), Statistics and Computing,
vol.
10,
no. 3, pp. 197-208, 2000.Pdf
(journal paper version of technical report Cambridge University
CUED/F-INFENG/TR310 "On sequential
simulation-based
methods for Bayesian filtering", 1998 Pdf)
This paper
is a fast
breaking
paper and has been reprinted in A. Harvey & T.
Proietti (eds), Readings
in Unobserved Components Models, Series
Advanced Texts in Econometrics, Oxford University Press, 2005.
"Convergence
of Sequential Monte Carlo Methods'' (wth D. Crisan), Technical report,
Cambridge University CUED/F-INFENG/TR381, 2000 (never appeared) Pdf
''Stochastic Sampling Algorithms for State Estimation of
Jump
Markov
Linear
Systems'' (with A. Logothetis & V. Krishnamurthy), IEEE
Trans.
Automatic
Control, vol. 45, no. 2, pp.
188-201, 2000. Pdf
"Simulated Annealing for Maximum A Posteriori Parameter
Estimation of
Hidden
Markov Models" (with C. Andrieu), IEEE Trans. Information
Theory,
vol. 46, no. 3, pp. 994-1004, 2000.
"Reversible jump
simulated
annealing
for RBFs", (with C. Andrieu & N. de Freitas), UAI 2000. Pdf
"Rao-Blackwellised
particle filtering for dynamic Bayesian networks", (with N. de Freitas,
K. Murphy & S. Russell), UAI 2000. Pdf
"The
Unscented
Particle
Filter", (with R van der Merwe, N. de Freitas & E Wan, ), NIPS 2000 PdfLonger
Report
MCMC data association for
target
tracking", (with N. Bergman), Proc.
IEEE ICASSP, 2000.Download
it here
"Sequential MCMC for
Bayesian
Model Selection", (with C. Andrieu & N. de Freitas, ) Proc.
IEEE HOS, 1999 (invited paper). Pdf
"Simulation-Based Methods for Blind Maximum-Likelihood
Linear
System Identification", (with O. Cappe, E. Moulines & M.
Lavielle), Signal
Processing, vol. 73, no.
1-2, pp. 3-25, 1999.
"An Improved Method for Simulation of Real Stable ARMA(p,q)
processes" (with C. Andrieu), IEEE
Signal Proc. Letters, vol. 6, no.6, pp. 142-144, 1999.
"Joint Bayesian Detection and Estimation of Noisy Sinusoids
via
Reversible
Jump MCMC" (with C. Andrieu), IEEE Trans. Signal Processing,
vol.
47, no. 10, pp. 2667-2676, 1999 Pdf
Rejected paper
"Filtrage Optimal et Sous-Optimal des Signaux de
Rayonnements" (never appeared): my first journal paper (written in Word) submitted to Traitement du Signal
in 1995 and rejected. I was about to give up academia after this
promising beginning but eventually didn't and tried harder.