Arnaud Doucet

Orcid: 0000-0002-7662-419X

According to our database1, Arnaud Doucet authored at least 231 papers between 1996 and 2024.

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Bibliography

2024
Mitigating LLM Hallucinations via Conformal Abstention.
CoRR, 2024

RecurrentGemma: Moving Past Transformers for Efficient Open Language Models.
CoRR, 2024

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models.
CoRR, 2024

Target Score Matching.
CoRR, 2024

Particle Denoising Diffusion Sampler.
CoRR, 2024

Implicit Diffusion: Efficient Optimization through Stochastic Sampling.
CoRR, 2024

2023
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics.
J. Mach. Learn. Res., 2023

Diffusion Generative Inverse Design.
CoRR, 2023

Reinforced Self-Training (ReST) for Language Modeling.
CoRR, 2023

Linear Convergence Bounds for Diffusion Models via Stochastic Localization.
CoRR, 2023

Conformal prediction under ambiguous ground truth.
CoRR, 2023

Evaluating AI systems under uncertain ground truth: a case study in dermatology.
CoRR, 2023

Error Bounds for Flow Matching Methods.
CoRR, 2023

Causal Falsification of Digital Twins.
CoRR, 2023

A Unified Framework for U-Net Design and Analysis.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Trans-Dimensional Generative Modeling via Jump Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Diffusion Schrödinger Bridge Matching.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

SE(3) diffusion model with application to protein backbone generation.
Proceedings of the International Conference on Machine Learning, 2023

Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC.
Proceedings of the International Conference on Machine Learning, 2023

Denoising Diffusion Samplers.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Wide stochastic networks: Gaussian limit and PAC-Bayesian training.
Proceedings of the International Conference on Algorithmic Learning Theory, 2023

2022
An empirical study of implicit regularization in deep offline RL.
Trans. Mach. Learn. Res., 2022

COIN++: Neural Compression Across Modalities.
Trans. Mach. Learn. Res., 2022

Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting.
J. Mach. Learn. Res., 2022

On Instrumental Variable Regression for Deep Offline Policy Evaluation.
J. Mach. Learn. Res., 2022

Continuous diffusion for categorical data.
CoRR, 2022

From Denoising Diffusions to Denoising Markov Models.
CoRR, 2022

Categorical SDEs with Simplex Diffusion.
CoRR, 2022

Maximum Likelihood Learning of Energy-Based Models for Simulation-Based Inference.
CoRR, 2022

Spectral Diffusion Processes.
CoRR, 2022

Solving Fredholm Integral Equations of the First Kind via Wasserstein Gradient Flows.
CoRR, 2022

A PAC-Bayes bound for deterministic classifiers.
CoRR, 2022

Riemannian Diffusion Schrödinger Bridge.
CoRR, 2022

Ranking in Contextual Multi-Armed Bandits.
CoRR, 2022

Conformal Off-Policy Prediction in Contextual Bandits.
CoRR, 2022

Riemannian Score-Based Generative Modeling.
CoRR, 2022

Importance Weighting Approach in Kernel Bayes' Rule.
CoRR, 2022

COIN++: Data Agnostic Neural Compression.
CoRR, 2022

Mitigating statistical bias within differentially private synthetic data.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Conditional simulation using diffusion Schrödinger bridges.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Conformal Off-Policy Prediction in Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Score-Based Diffusion meets Annealed Importance Sampling.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Towards Learning Universal Hyperparameter Optimizers with Transformers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Continuous Time Framework for Discrete Denoising Models.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Riemannian Score-Based Generative Modelling.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Importance Weighted Kernel Bayes' Rule.
Proceedings of the International Conference on Machine Learning, 2022

Continual Repeated Annealed Flow Transport Monte Carlo.
Proceedings of the International Conference on Machine Learning, 2022

Learning Optimal Conformal Classifiers.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving.
Proceedings of the Conference on Robot Learning, 2022

Chained generalisation bounds.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Generative Models as Distributions of Functions.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Conditionally Gaussian PAC-Bayes.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

On PAC-Bayesian reconstruction guarantees for VAEs.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Asymptotic Properties of Recursive Particle Maximum Likelihood Estimation.
IEEE Trans. Inf. Theory, 2021

Dual Space Preconditioning for Gradient Descent.
SIAM J. Optim., 2021

Bias of Particle Approximations to Optimal Filter Derivative.
SIAM J. Control. Optim., 2021

Network Consensus in the Wasserstein Metric Space of Probability Measures.
SIAM J. Control. Optim., 2021

Nonreversible Jump Algorithms for Bayesian Nested Model Selection.
J. Comput. Graph. Stat., 2021

Simulating Diffusion Bridges with Score Matching.
CoRR, 2021

Conditional Gaussian PAC-Bayes.
CoRR, 2021

Bias Mitigated Learning from Differentially Private Synthetic Data: A Cautionary Tale.
CoRR, 2021

Quantitative Uniform Stability of the Iterative Proportional Fitting Procedure.
CoRR, 2021

COIN: COmpression with Implicit Neural representations.
CoRR, 2021

Unbiased gradient estimation for variational auto-encoders using coupled Markov chains.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Variational inference with continuously-indexed normalizing flows.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Online Variational Filtering and Parameter Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Monte Carlo Variational Auto-Encoders.
Proceedings of the 38th International Conference on Machine Learning, 2021

Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding.
Proceedings of the 38th International Conference on Machine Learning, 2021

Differentiable Particle Filtering via Entropy-Regularized Optimal Transport.
Proceedings of the 38th International Conference on Machine Learning, 2021

Annealed Flow Transport Monte Carlo.
Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Deep Features in Instrumental Variable Regression.
Proceedings of the 9th International Conference on Learning Representations, 2021

Robust Pruning at Initialization.
Proceedings of the 9th International Conference on Learning Representations, 2021

The Curse of Depth in Kernel Regime.
Proceedings of the I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, 2021

Stable ResNet.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Pruning untrained neural networks: Principles and Analysis.
CoRR, 2020

Modular Meta-Learning with Shrinkage.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Analyticity of Entropy Rates of Continuous-State Hidden Markov Models.
IEEE Trans. Inf. Theory, 2019

Localised Generative Flows.
CoRR, 2019

Training Dynamics of Deep Networks using Stochastic Gradient Descent via Neural Tangent Kernel.
CoRR, 2019

Augmented Neural ODEs.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Replica Conditional Sequential Monte Carlo.
Proceedings of the 36th International Conference on Machine Learning, 2019

On the Impact of the Activation function on Deep Neural Networks Training.
Proceedings of the 36th International Conference on Machine Learning, 2019

Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets.
Proceedings of the 36th International Conference on Machine Learning, 2019

Stability of Optimal Filter Higher-Order Derivatives.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Bernoulli Race Particle Filters.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Unbiased Smoothing using Particle Independent Metropolis-Hastings.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Hamiltonian Descent Methods.
CoRR, 2018

On the Selection of Initialization and Activation Function for Deep Neural Networks.
CoRR, 2018

Hamiltonian Variational Auto-Encoder.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Generalized Pólya Urn for Time-Varying Pitman-Yor Processes.
J. Mach. Learn. Res., 2017

Particle Gibbs Split-Merge Sampling for Bayesian Inference in Mixture Models.
J. Mach. Learn. Res., 2017

On Markov chain Monte Carlo methods for tall data.
J. Mach. Learn. Res., 2017

Filtering Variational Objectives.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Particle Value Functions.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Interacting Particle Markov Chain Monte Carlo.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Uniform Stability of a Particle Approximation of the Optimal Filter Derivative.
SIAM J. Control. Optim., 2015

Expectation Particle Belief Propagation.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Joint Channel and Doppler Offset Estimation in Dynamic Cooperative Relay Networks.
IEEE Trans. Wirel. Commun., 2014

Asynchronous Anytime Sequential Monte Carlo.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Fast Computation of Wasserstein Barycenters.
Proceedings of the 31th International Conference on Machine Learning, 2014

Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Introduction to Special Issue on Monte Carlo Methods in Statistics.
ACM Trans. Model. Comput. Simul., 2013

Expectation-maximization algorithms for inference in Dirichlet processes mixture.
Pattern Anal. Appl., 2013

2012
Distributed Maximum Likelihood for Simultaneous Self-Localization and Tracking in Sensor Networks.
IEEE Trans. Signal Process., 2012

An adaptive sequential Monte Carlo method for approximate Bayesian computation.
Stat. Comput., 2012

On-line changepoint detection and parameter estimation with application to genomic data.
Stat. Comput., 2012

2011
Particle Approximation of the Intensity Measures of a Spatial Branching Point Process Arising in Multitarget Tracking.
SIAM J. Control. Optim., 2011

Melody Tracking Based on Sequential Bayesian Model.
IEEE J. Sel. Top. Signal Process., 2011

Asymptotic bias of stochastic gradient search.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

2010
A Fixed-Lag Particle Filter for the Joint Detection/Compensation of Interference Effects in GPS Navigation.
IEEE Trans. Signal Process., 2010

A Bayesian approach to joint tracking and identification of geometric shapes in video sequences.
Image Vis. Comput., 2010

Channel Tracking for Relay Networks via Adaptive Particle MCMC
CoRR, 2010

On solving integral equations using Markov chain Monte Carlo methods.
Appl. Math. Comput., 2010

2009
Particle-method-based formulation of risk-sensitive filter.
Signal Process., 2009

An Expectation Maximization Algorithm for Continuous Markov Decision Processes with Arbitrary Reward.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

A boosting approach to structure learning of graphs with and without prior knowledge.
Bioinform., 2009

A Bayesian exploration-exploitation approach for optimal online sensing and planning with a visually guided mobile robot.
Auton. Robots, 2009

New inference strategies for solving Markov Decision Processes using reversible jump MCMC.
Proceedings of the UAI 2009, 2009

Bayesian Nonparametric Models on Decomposable Graphs.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Inference and Learning for Active Sensing, Experimental Design and Control.
Proceedings of the Pattern Recognition and Image Analysis, 4th Iberian Conference, 2009

2008
Bayesian Inference for Linear Dynamic Models With Dirichlet Process Mixtures.
IEEE Trans. Signal Process., 2008

Particle methods for maximum likelihood estimation in latent variable models.
Stat. Comput., 2008

Interacting sequential Monte Carlo samplers for trans-dimensional simulation.
Comput. Stat. Data Anal., 2008

Sparse Bayesian nonparametric regression.
Proceedings of the Machine Learning, 2008

2007
GSR: A New Genetic Algorithm for Improving Source and Channel Estimates.
IEEE Trans. Circuits Syst. I Regul. Pap., 2007

A Framework for Kernel-Based Multi-Category Classification.
J. Artif. Intell. Res., 2007

A policy gradient method for semi-Markov decision processes with application to call admission control.
Eur. J. Oper. Res., 2007

Simulation-based optimal sensor scheduling with application to observer trajectory planning.
Autom., 2007

Generalized Polya Urn for Time-varying Dirichlet Process Mixtures.
Proceedings of the UAI 2007, 2007

Active Policy Learning for Robot Planning and Exploration under Uncertainty.
Proceedings of the Robotics: Science and Systems III, 2007

Bayesian Policy Learning with Trans-Dimensional MCMC.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

A Monte Carlo Algorithm for Optimal Quantization in Hidden Markov Models.
Proceedings of the IEEE International Symposium on Information Theory, 2007

Bayesian Unsupervised Signal Classification by Dirichlet Process Mixtures of Gaussian Processes.
Proceedings of the IEEE International Conference on Acoustics, 2007

2006
Sequential sampling for dynamic environment maps.
Proceedings of the International Conference on Computer Graphics and Interactive Techniques, 2006

Sequential Sampling for Dynamic Environment Map Illumination.
Proceedings of the Eurographics Symposium on Rendering Techniques, Nicosia, Cyprus, 2006, 2006

Fast particle smoothing: if I had a million particles.
Proceedings of the Machine Learning, 2006

Particle Filter as A Controlled Markov Chain For On-Line Parameter Estimation in General State Space Models.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Maximum Likelihood Parameter Estimation for Latent Variable Models Using Sequential Monte Carlo.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Optimal Filtering For Partially Observed Point Processes Using Trans-Dimensional Sequential Monte Carlo.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

A Distributed Recursive Maximum Likelihood Implementation for Sensor Registration.
Proceedings of the 9th International Conference on Information Fusion, 2006

Bayesian Inference for Dynamic Models with Dirichlet Process Mixtures.
Proceedings of the 9th International Conference on Information Fusion, 2006

Gradient-free maximum likelihood parameter estimation with particle filters.
Proceedings of the American Control Conference, 2006

2005
Monte Carlo methods for signal processing: a review in the statistical signal processing context.
IEEE Signal Process. Mag., 2005

Toward Practical N2 Monte Carlo: the Marginal Particle Filter.
Proceedings of the UAI '05, 2005

Joint Bayesian model selection and blind equalization of ISI channels.
Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005

Adapting two-class support vector classification methods to many class problems.
Proceedings of the Machine Learning, 2005

Particle methods for optimal filter derivative: application to parameter estimation.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

Space alternating data augmentation: application to finite mixture of Gaussians and speaker recognition.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

On-Line Parameter Estimation in General State-Space Models.
Proceedings of the 44th IEEE IEEE Conference on Decision and Control and 8th European Control Conference Control, 2005

2004
Particle methods for change detection, system identification, and control.
Proc. IEEE, 2004

Particle Filtering for Joint Symbol and Code Delay Estimation in DS Spread Spectrum Systems in Multipath Environment.
EURASIP J. Adv. Signal Process., 2004

Editorial.
EURASIP J. Adv. Signal Process., 2004

Blind SOS subspace channel estimation and equalization techniques exploiting spatial diversity in OFDM systems.
Digit. Signal Process., 2004

The cross-entropy method for blind multiuser detection.
Proceedings of the 2004 IEEE International Symposium on Information Theory, 2004

A Rao-Blackwellized particle filter for INS/GPS integration.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

Nonlinear filtering approaches for INS/GPS integration.
Proceedings of the 2004 12th European Signal Processing Conference, 2004

Fixed-lag sequential Monte Carlo.
Proceedings of the 2004 12th European Signal Processing Conference, 2004

2003
A new class of soft MIMO demodulation algorithms.
IEEE Trans. Signal Process., 2003

Efficient particle filtering for jump Markov systems. Application to time-varying autoregressions.
IEEE Trans. Signal Process., 2003

Copulas: a new insight into positive time-frequency distributions.
IEEE Signal Process. Lett., 2003

An Introduction to MCMC for Machine Learning.
Mach. Learn., 2003

Sequential Bayesian Kernel Regression.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Maintaining Multi-Modality through Mixture Tracking.
Proceedings of the 9th IEEE International Conference on Computer Vision (ICCV 2003), 2003

Particle filtering for joint symbol and parameter estimation in DS spread spectrum systems.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

Optimisation of particle filters using simultaneous perturbation stochastic approximation.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

Online expectation-maximization type algorithms for parameter estimation in general state space models.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

Stochastic approximation for optimal observer trajectory planning.
Proceedings of the 42nd IEEE Conference on Decision and Control, 2003

Sampling-based near-optimal MIMO demodulation algorithms.
Proceedings of the 42nd IEEE Conference on Decision and Control, 2003

Two time-scale stochastic approximation for constrained stochastic optimization and constrained Markov decision problems.
Proceedings of the American Control Conference, 2003

2002
Bayesian curve fitting using MCMC with applications to signal segmentation.
IEEE Trans. Signal Process., 2002

Monte Carlo smoothing with application to audio signal enhancement.
IEEE Trans. Signal Process., 2002

A survey of convergence results on particle filtering methods for practitioners.
IEEE Trans. Signal Process., 2002

Particle methods for Bayesian modeling and enhancement of speech signals.
IEEE Trans. Speech Audio Process., 2002

Optimized support vector machines for nonstationary signal classification.
IEEE Signal Process. Lett., 2002

Marginal maximum a posteriori estimation using Markov chain Monte Carlo.
Stat. Comput., 2002

Sparse Bayesian Learning for Regression and Classification using Markov Chain Monte Carlo.
Proceedings of the Machine Learning, 2002

Efficient particle filtering for Jump Markov Systems.
Proceedings of the IEEE International Conference on Acoustics, 2002

A policy gradient method for SMDPs with application to call admission control.
Proceedings of the Seventh International Conference on Control, 2002

On the use and misuse of particle filtering in digital communications.
Proceedings of the 11th European Signal Processing Conference, 2002

A particle filtering technique for Jump Markov Systems.
Proceedings of the 11th European Signal Processing Conference, 2002

Exponential forgetting and geometric ergodicity in state-space models.
Proceedings of the 41st IEEE Conference on Decision and Control, 2002

On-line optimization of sequential Monte Carlo methods using stochastic approximation.
Proceedings of the American Control Conference, 2002

2001
Particle filters for state estimation of jump Markov linear systems.
IEEE Trans. Signal Process., 2001

Iterative algorithms for state estimation of jump Markov linear systems.
IEEE Trans. Signal Process., 2001

Bayesian deconvolution of noisy filtered point processes.
IEEE Trans. Signal Process., 2001

Particle filtering for demodulation in fading channels with non-Gaussian additive noise.
IEEE Trans. Commun., 2001

Model selection by MCMC computation.
Signal Process., 2001

Robust Full Bayesian Learning for Radial Basis Networks.
Neural Comput., 2001

Optimal Estimation of Amplitude and Phase Modulated Signals.
Monte Carlo Methods Appl., 2001

Rao-Blackwellised Particle Filtering via Data Augmentation.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Convergence properties of Bayesian evolutionary algorithms with population size greater than 1.
Proceedings of the 2001 Congress on Evolutionary Computation, 2001

An Introduction to Sequential Monte Carlo Methods.
Proceedings of the Sequential Monte Carlo Methods in Practice, 2001

Sequential Monte Carlo Methods for Optimal Filtering.
Proceedings of the Sequential Monte Carlo Methods in Practice, 2001

2000
Simulated annealing for maximum a Posteriori parameter estimation of hidden Markov models.
IEEE Trans. Inf. Theory, 2000

Stochastic sampling algorithms for state estimation of jump Markov linear systems.
IEEE Trans. Autom. Control., 2000

On sequential Monte Carlo sampling methods for Bayesian filtering.
Stat. Comput., 2000

Sequential Monte Carlo Methods to Train Neural Network Models.
Neural Comput., 2000

Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

Reversible Jump MCMC Simulated Annealing for Neural Networks.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

The Unscented Particle Filter.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Particle filtering for non-stationary speech modelling and enhancement.
Proceedings of the Sixth International Conference on Spoken Language Processing, 2000

Particle filters for demodulation of M-ary modulated signals in noisy fading communication channels.
Proceedings of the IEEE International Conference on Acoustics, 2000

Monte Carlo filtering and smoothing with application to time-varying spectral estimation.
Proceedings of the IEEE International Conference on Acoustics, 2000

Markov chain Monte Carlo data association for target tracking.
Proceedings of the IEEE International Conference on Acoustics, 2000

On-line non-stationary ICA using mixture models.
Proceedings of the IEEE International Conference on Acoustics, 2000

Sequential simulation-based estimation of jump Markov linear systems.
Proceedings of the 39th IEEE Conference on Decision and Control, 2000

1999
Joint Bayesian model selection and estimation of noisy sinusoids via reversible jump MCMC.
IEEE Trans. Signal Process., 1999

An improved method for uniform simulation of stable minimum phase real ARMA (p, q) processes.
IEEE Signal Process. Lett., 1999

Simulation-based methods for blind maximum-likelihood filter identification.
Signal Process., 1999

A Bayesian approach to harmonic retrieval with clipped data.
Signal Process., 1999

Robust Full Bayesian Methods for Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Sequential Bayesian wavelet denoising.
Proceedings of the ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications, 1999

Marginal MAP estimation using Markov chain Monte Carlo.
Proceedings of the 1999 IEEE International Conference on Acoustics, 1999

Iterative algorithms for optimal state estimation of jump Markov linear systems.
Proceedings of the 1999 IEEE International Conference on Acoustics, 1999

1998
Global Optimisation of Neural Network Models via Sequential Sampling.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Joint Bayesian detection and estimation of sinusoids embedded in noise.
Proceedings of the 1998 IEEE International Conference on Acoustics, 1998

Bayesian deconvolution of poissonian point sources.
Proceedings of the 9th European Signal Processing Conference, 1998

Robust Bayesian spectral analysis via MCMC sampling.
Proceedings of the 9th European Signal Processing Conference, 1998

Efficient stochastic maximum a posteriori estimation for harmonic signals.
Proceedings of the 9th European Signal Processing Conference, 1998

1997
Bayesian estimation of state-space models applied to deconvolution of Bernoulli - Gaussian processes.
Signal Process., 1997

1996
Instantaneous frequency estimation: Bayesian approaches versus reassignment-application to gravitational waves.
Proceedings of the 1996 IEEE International Conference on Acoustics, 1996

Fully Bayesian analysis of conditionally linear Gaussian state space models.
Proceedings of the 1996 IEEE International Conference on Acoustics, 1996

Fully Bayesian analysis of Hidden Markov models.
Proceedings of the 8th European Signal Processing Conference, 1996

Bayesian deconvolution of cyclostationary processes based on point processes.
Proceedings of the 8th European Signal Processing Conference, 1996


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