Arnaud Doucet

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Arnaud Doucet is affiliated with the following schools: University of Oxford, Université Paris Cité, University of British Columbia

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Arnaud Doucet's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

On sequential Monte Carlo sampling methods for Bayesian filtering (2000) (4767)
Sequential Monte Carlo Methods in Practice (2001) (3667)
An Introduction to MCMC for Machine Learning (2004) (2502)
A Tutorial on Particle Filtering and Smoothing: Fifteen years later (2008) (1982)
Particle Markov chain Monte Carlo methods (2010) (1869)
The Unscented Particle Filter (2000) (1757)
Sequential Monte Carlo samplers (2002) (1614)
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks (2000) (1438)
An Introduction to Sequential Monte Carlo Methods (2001) (1217)
Sequential Monte Carlo methods for multitarget filtering with random finite sets (2005) (1208)
Editors: Sequential Monte Carlo Methods in Practice (2001) (1138)
A survey of convergence results on particle filtering methods for practitioners (2002) (1004)
Particle filters for state estimation of jump Markov linear systems (2001) (811)
On sequential simulation-based methods for Bayesian filtering (1998) (797)
Monte Carlo Smoothing for Nonlinear Time Series (2004) (608)
Fast Computation of Wasserstein Barycenters (2013) (607)
Maintaining multimodality through mixture tracking (2003) (471)
An adaptive sequential Monte Carlo method for approximate Bayesian computation (2012) (468)
Augmented Neural ODEs (2019) (390)
On Particle Methods for Parameter Estimation in State-Space Models (2014) (366)
Particle methods for change detection, system identification, and control (2004) (338)
Sequential Monte Carlo in Practice (2001) (335)
Sequential monte carlo implementation of the phd filter for multi-target tracking (2003) (331)
On the Utility of Graphics Cards to Perform Massively Parallel Simulation of Advanced Monte Carlo Methods (2009) (329)
Smoothing algorithms for state–space models (2010) (320)
Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator (2012) (303)
An overview of sequential Monte Carlo methods for parameter estimation in general state-space models (2009) (290)
Parameter estimation in general state-space models using particle methods (2003) (272)
Particle filtering for partially observed Gaussian state space models (2002) (264)
Joint Bayesian model selection and estimation of noisy sinusoids via reversible jump MCMC (1999) (256)
On sequential Monte Carlo methods for Bayesian filtering (1998) (241)
A Bayesian exploration-exploitation approach for optimal online sensing and planning with a visually guided mobile robot (2009) (237)
On Markov chain Monte Carlo methods for tall data (2015) (232)
Particle approximations of the score and observed information matrix in state space models with application to parameter estimation (2011) (223)
Sequential Monte Carlo Methods to Train Neural Network Models (2000) (221)
The Bouncy Particle Sampler: A Nonreversible Rejection-Free Markov Chain Monte Carlo Method (2015) (209)
Bayesian curve fitting using MCMC with applications to signal segmentation (2002) (194)
Fast particle smoothing: if I had a million particles (2006) (188)
Particle methods for Bayesian modeling and enhancement of speech signals (2002) (180)
Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach (2014) (175)
Efficient particle filtering for jump Markov systems. Application to time-varying autoregressions (2003) (175)
On adaptive resampling strategies for sequential Monte Carlo methods (2012) (174)
A note on auxiliary particle filters (2008) (173)
Filtering Variational Objectives (2017) (170)
Active Policy Learning for Robot Planning and Exploration under Uncertainty (2007) (168)
Efficient Block Sampling Strategies for Sequential Monte Carlo Methods (2006) (161)
Monte Carlo smoothing with application to audio signal enhancement (2001) (155)
Particle filtering for multi-target tracking and sensor management (2002) (153)
Maximum a Posteriori Sequence Estimation Using Monte Carlo Particle Filters (2001) (152)
Monte Carlo methods for signal processing: a review in the statistical signal processing context (2005) (151)
Stochastic sampling algorithms for state estimation of jump Markov linear systems (2000) (146)
Sequential Monte Carlo Methods (2006) (140)
Toward Practical N2 Monte Carlo: the Marginal Particle Filter (2005) (137)
Inference for Lévy‐Driven Stochastic Volatility Models via Adaptive Sequential Monte Carlo (2011) (135)
Sequential MCMC for Bayesian model selection (1999) (127)
On the Impact of the Activation Function on Deep Neural Networks Training (2019) (124)
Generalized Polya Urn for Time-varying Dirichlet Process Mixtures (2007) (121)
Iterative algorithms for state estimation of jump Markov linear systems (2001) (120)
Efficient Bayesian Inference for Generalized Bradley–Terry Models (2010) (118)
Bayesian Inference for Linear Dynamic Models With Dirichlet Process Mixtures (2007) (111)
Sparse Bayesian nonparametric regression (2008) (108)
On-Line Parameter Estimation in General State-Space Models (2005) (106)
Marginal maximum a posteriori estimation using Markov chain Monte Carlo (2002) (104)
Model selection by MCMC computation (2001) (103)
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling (2021) (100)
Monte Carlo methods for signal processing (2005) (98)
The correlated pseudomarginal method (2015) (98)
Robust Full Bayesian Learning for Radial Basis Networks (2001) (95)
A new class of soft MIMO demodulation algorithms (2003) (93)
Probability hypothesis density filter versus multiple hypothesis tracking (2004) (93)
A survey of convergence results on particle ltering for practitioners (2002) (87)
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows (2019) (86)
Piecewise-Deterministic Markov Chain Monte Carlo (2017) (80)
Sequential Monte Carlo Methods for Optimal Filtering (2001) (79)
Reversible Jump Markov Chain Monte Carlo Strategies for Bayesian Model Selection in Autoregressive Processes (2004) (76)
Online expectation-maximization type algorithms for parameter estimation in general state space models (2003) (75)
On uncertainty quantification in hydrogeology and hydrogeophysics (2017) (74)
Efficient Bayesian Inference for Switching State-Space Models using Discrete Particle Markov Chain Monte Carlo Methods (2010) (74)
Convergence of Sequential Monte Carlo Methods (2007) (73)
Forward Smoothing using Sequential Monte Carlo (2010) (71)
COIN: COmpression with Implicit Neural representations (2021) (71)
Simulation-Based Optimal Sensor Scheduling with Application to Observer Trajectory Planning (2005) (71)
Efficient particle filtering for Jump Markov Systems (2002) (68)
Computational Advances for and from Bayesian Analysis (2004) (68)
On the Selection of Initialization and Activation Function for Deep Neural Networks (2018) (67)
Hamiltonian Variational Auto-Encoder (2018) (66)
Convergence of the SMC Implementation of the PHD Filte (2006) (65)
Particle methods for optimal filter derivative: application to parameter estimation (2005) (64)
Particle methods for maximum likelihood estimation in latent variable models (2008) (64)
On Adaptive Resampling Procedures for Sequential Monte Carlo Methods (2008) (64)
Distributed Maximum Likelihood for Simultaneous Self-Localization and Tracking in Sensor Networks (2012) (64)
Sequential auxiliary particle belief propagation (2005) (63)
A backward particle interpretation of Feynman-Kac formulae (2009) (62)
Sequential Monte Carlo samplers for rare events (2006) (58)
Controlled sequential Monte Carlo (2017) (58)
Monte Carlo filtering and smoothing with application to time-varying spectral estimation (2000) (57)
Markov chain Monte Carlo data association for target tracking (2000) (57)
Generative Models as Distributions of Functions (2021) (56)
Random finite sets and sequential Monte Carlo methods in multi-target tracking (2003) (56)
Interacting sequential Monte Carlo samplers for trans-dimensional simulation (2008) (56)
A Rao-Blackwellized particle filter for INS/GPS integration (2004) (55)
Optimized support vector machines for nonstationary signal classification (2002) (55)
Efficient Bayesian Inference for Multivariate Probit Models With Sparse Inverse Correlation Matrices (2012) (52)
A lognormal central limit theorem for particle approximations of normalizing constants (2013) (52)
Sequentially interacting Markov chain Monte Carlo methods (2010) (52)
Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains (2017) (50)
Copulas: a new insight into positive time-frequency distributions (2003) (50)
Bayesian estimation of state-space models applied to deconvolution of Bernoulli - Gaussian processes (1997) (48)
Optimal Estimation and Cramér-Rao Bounds for Partial Non-Gaussian State Space Models (2001) (48)
Hamiltonian Descent Methods (2018) (47)
A Hierarchical Bayesian Framework for Constructing Sparsity-inducing Priors (2010) (46)
Randomized Hamiltonian Monte Carlo as scaling limit of the bouncy particle sampler and dimension-free convergence rates (2018) (45)
Asynchronous Anytime Sequential Monte Carlo (2014) (45)
An Online Expectation–Maximization Algorithm for Changepoint Models (2013) (45)
Recursive state estimation for multiple switching models with unknown transition probabilities (2002) (44)
Bayesian Inference for Dynamic Models with Dirichlet Process Mixtures (2006) (44)
Reversible Jump MCMC Simulated Annealing for Neural Networks (2000) (44)
Simulated annealing for maximum a Posteriori parameter estimation of hidden Markov models (2000) (43)
Particle methods: An introduction with applications (2014) (43)
Riemannian Score-Based Generative Modeling (2022) (43)
Autoregressive Kernels For Time Series (2011) (43)
Particle Motions in Absorbing Medium with Hard and Soft Obstacles (2004) (43)
On solving integral equations using Markov chain Monte Carlo methods (2010) (42)
Asymptotic bias of stochastic gradient search (2011) (42)
An Adaptive Interacting Wang–Landau Algorithm for Automatic Density Exploration (2011) (42)
On a Class of Genealogical and Interacting Metropolis Models (2003) (42)
A policy gradient method for semi-Markov decision processes with application to call admission control (2007) (41)
Bayesian Approaches to Multi-Sensor Data Fusion (1999) (41)
The Correlated Pseudo-Marginal Method (2018) (39)
Exponential ergodicity of the bouncy particle sampler (2017) (38)
On-line changepoint detection and parameter estimation with application to genomic data (2012) (38)
Bayesian deconvolution of noisy filtered point processes (2001) (37)
SMC Samplers for Bayesian Optimal Nonlinear Design (2006) (37)
New inference strategies for solving Markov Decision Processes using reversible jump MCMC (2009) (36)
Blind SOS subspace channel estimation and equalization techniques exploiting spatial diversity in OFDM systems (2004) (36)
Exponential forgetting and geometric ergodicity for optimal filtering in general state-space models (2005) (36)
A Framework for Kernel-Based Multi-Category Classification (2007) (36)
On sequential sampling Monte Carlo sampling methods for Bayesian filtering (2000) (36)
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport (2021) (35)
Sequential Monte Carlo methods for optimisation of neural network models (1998) (34)
Gibbs flow for approximate transport with applications to Bayesian computation (2015) (33)
Sequential Bayesian Estimation And Model Selection Applied To Neural Networks (1999) (33)
Bayesian Policy Learning with Trans-Dimensional MCMC (2007) (33)
On Adaptive Sequential Monte Carlo Methods (2008) (33)
An Expectation Maximization Algorithm for Continuous Markov Decision Processes with Arbitrary Reward (2009) (33)
Particle Markov Chain Monte Carlo for Efficient Numerical Simulation (2009) (33)
Interacting Particle Markov Chain Monte Carlo (2016) (31)
Mean-field Behaviour of Neural Tangent Kernel for Deep Neural Networks (2019) (31)
Bayesian Phylogenetic Inference Using a Combinatorial Sequential Monte Carlo Method (2015) (31)
Sequential Monte Carlo methods for Bayesian computation (2006) (31)
Simulation-based methods for blind maximum-likelihood filter identification (1999) (30)
Rao-Blackwellised Particle Filtering via Data Augmentation (2001) (30)
Learning Deep Features in Instrumental Variable Regression (2020) (30)
Modular Meta-Learning with Shrinkage (2019) (29)
Robust Full Bayesian Learning for Neural Networks (1999) (28)
Monte Carlo smoothing with application to speech enhancement (2002) (28)
An efficient computational approach for prior sensitivity analysis and cross‐validation (2010) (27)
A boosting approach to structure learning of graphs with and without prior knowledge (2009) (27)
Simulated likelihood inference for stochastic volatility models using continuous particle filtering (2014) (27)
Sequential sampling for dynamic environment map illumination (2006) (27)
Uniform Stability of a Particle Approximation of the Optimal Filter Derivative (2011) (27)
Derivative-Free Estimation of the Score Vector and Observed Information Matrix with Application to State-Space Models (2013) (27)
Non‐reversible parallel tempering: A scalable highly parallel MCMC scheme (2019) (26)
Convergence of simulated annealing using Foster-Lyapunov criteria (2001) (26)
Unbiased Markov chain Monte Carlo for intractable target distributions (2018) (26)
Sequential Monte Carlo for maneuvering target tracking in clutter (1999) (26)
European Signal Processing Conference (2015) (25)
Large-sample asymptotics of the pseudo-marginal method (2018) (25)
Particle filtering for multiuser detection in fading CDMA channels (2001) (25)
On the use and misuse of particle filtering in digital communications (2002) (24)
Particle Filtering for Joint Symbol and Code Delay Estimation in DS Spread Spectrum Systems in Multipath Environment (2004) (24)
Particle Filtering and Smoothing: Fifteen years later (2008) (24)
A Note on E ¢ cient Conditional Simulation of Gaussian Distributions (2010) (23)
Annealed Flow Transport Monte Carlo (2021) (23)
Bayesian Sparsity-Path-Analysis of Genetic Association Signal using Generalized t Priors (2011) (23)
Grouping Priors and the Bayesian Elastic Net (2010) (23)
Robust Pruning at Initialization (2020) (23)
Novel particle filter methods for recursive and batch maximum likelihood parameter estimation in general states space models (2005) (22)
Methodology for Monte Carlo smoothing with application to time-varying autoregressions (2000) (22)
Monte Carlo Variational Auto-Encoders (2021) (22)
Generalized Pólya Urn for Time-Varying Pitman-Yor Processes (2017) (22)
Gradient-free maximum likelihood parameter estimation with particle filters (2006) (21)
On the conditional distributions of spatial point processes (2011) (21)
Bayesian Unsupervised Signal Classification by Dirichlet Process Mixtures of Gaussian Processes (2007) (21)
Introduction to Special Issue on Monte Carlo Methods in Statistics (2013) (21)
On nonlinear Markov chain Monte Carlo (2011) (21)
Particle filtering for demodulation in fading channels with non-Gaussian additive noise (2001) (21)
A Fixed-Lag Particle Filter for the Joint Detection/Compensation of Interference Effects in GPS Navigation (2010) (21)
Calibration and Filtering for Multi Factor Commodity Models with Seasonality: Incorporating Panel Data from Futures Contracts (2011) (20)
Expectation Particle Belief Propagation (2015) (20)
GSR: A New Genetic Algorithm for Improving Source and Channel Estimates (2007) (20)
NON-LINEAR MARKOV CHAIN MONTE CARLO (2007) (20)
Pseudo-Marginal Hamiltonian Monte Carlo (2016) (20)
Sparse Bayesian Learning for Regression and Classification using Markov Chain Monte Carlo (2002) (20)
Sequential Bayesian Kernel Regression (2003) (20)
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding (2021) (20)
Joint Bayesian detection and estimation of noisy sinusoids via reversible jump MCMC (1998) (19)
Unbiased Smoothing using Particle Independent Metropolis-Hastings (2019) (19)
Improved auxiliary particle filtering: applications to time-varying spectral analysis (2001) (19)
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting (2019) (19)
Interacting Markov chain Monte Carlo methods for solving nonlinear measure-valued equations (2010) (19)
Radial basis function regression using trans-dimensional sequential Monte Carlo (2003) (18)
On the utility of Metropolis-Hastings with asymmetric acceptance ratio (2018) (18)
Simulation-based optimal filter for maneuvering target tracking (1999) (18)
COIN++: Data Agnostic Neural Compression (2022) (18)
Stable ResNet (2020) (17)
A Note on Convergence of the Equi-Energy Sampler (2007) (17)
Robust Full Bayesian Methods for Neural Networks (1999) (17)
Optimisation of particle filters using simultaneous perturbation stochastic approximation (2003) (16)
Robust inference on parameters via particle filters and sandwich covariance matrices (2012) (16)
Particle Gibbs Split-Merge Sampling for Bayesian Inference in Mixture Models (2015) (16)
Exact approximation of Rao-Blackwellised particle filters (2012) (16)
Stability of sequential Monte Carlo samplers via the Foster-Lyapunov condition (2008) (16)
Trans-dimensional MCMC for Bayesian policy learning (2007) (16)
Learning Optimal Conformal Classifiers (2021) (16)
A Bayesian approach to joint tracking and identification of geometric shapes in video sequences (2010) (16)
Limit theorems for sequential MCMC methods (2018) (16)
On nonlinear Markov chain Monte Carlo via Self-interacting approximations. (2011) (16)
Conditional Simulation Using Diffusion Schrödinger Bridges (2022) (16)
Iterative algorithms for optimal state estimation of jump Markov linear systems (1999) (15)
Twisted Variational Sequential Monte Carlo (2018) (15)
Particle Value Functions (2017) (15)
Expectation-maximization algorithms for inference in Dirichlet processes mixture (2013) (15)
Quantitative Uniform Stability of the Iterative Proportional Fitting Procedure (2021) (15)
Distributed nonlinear consensus in the space of probability measures (2014) (15)
An Introduction to Monte Carlo Methods for Bayesian Data Analysis (2001) (15)
Sequential Monte Carlo computation of the score and observed information matrix in state-space models with application to parameter estimation (2009) (14)
Particle-method-based formulation of risk-sensitive filter (2009) (14)
Perfect simulation using atomic regeneration with application to Sequential Monte Carlo (2014) (14)
Sharp Propagation of Chaos Estimates for Feynman–Kac Particle Models (2007) (14)
The cross-entropy method for blind multiuser detection (2004) (14)
Continuous diffusion for categorical data (2022) (14)
Sequential Monte Carlo methods for diffusion processes (2009) (14)
Simulation of the annual loss distribution in operational risk via Panjer recursions and Volterra integral equations for value-at-risk and expected shortfall estimation (2007) (13)
A Continuous Time Framework for Discrete Denoising Models (2022) (13)
Unbiased Gradient Estimation for Variational Auto-Encoders using Coupled Markov Chains (2020) (13)
Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets (2019) (13)
Bayesian Computational Approaches to Model Selection (2000) (13)
Stochastic approximation for optimal observer trajectory planning (2003) (13)
Variational Inference with Continuously-Indexed Normalizing Flows (2020) (13)
Pruning untrained neural networks: Principles and Analysis (2020) (13)
On embedded hidden Markov models and particle Markov chain Monte Carlo methods (2016) (12)
Bayesian Computational Methods for Inference in Multiple Change-points Models (2011) (12)
Towards Learning Universal Hyperparameter Optimizers with Transformers (2022) (12)
A Functional Central Limit Theorem for a Class of Interacting Markov Chain Monte Carlo Methods (2009) (12)
Reversible jump Markov chain Monte Carlo for Bayesian deconvolution of point sources (1998) (12)
Particle Methods for Risk Sensitive Filtering (2005) (12)
Bayesian model selection of autoregressive processes (2000) (11)
An improved method for uniform simulation of stable minimum phase real ARMA (p,q) processes (1999) (11)
Simulating Diffusion Bridges with Score Matching (2021) (11)
Asymptotic Properties of Recursive Maximum Likelihood Estimation in Non-Linear State-Space Models (2018) (10)
Nonlinear filtering approaches for INS/GPS integration (2004) (10)
On-line non-stationary ICA using mixture models (2000) (10)
Fully Bayesian analysis of Hidden Markov models (1996) (10)
Sequential Monte Carlo tracking schemes for maneuvering targets with passive ranging (2002) (10)
On-line optimization of sequential Monte Carlo methods using stochastic approximation (2002) (10)
Instantaneous frequency estimation: Bayesian approaches versus reassignment-application to gravitational waves (1996) (9)
Non-Reversible Parallel Tempering: an Embarassingly Parallel MCMC Scheme (2019) (9)
Maximum Likelihood Parameter Estimation for Latent Variable Models Using Sequential Monte Carlo (2006) (9)
Channel Tracking for Relay Networks via Adaptive Particle MCMC (2010) (9)
Particle filters for stochastic differential equations of nonlinear diffusions (2005) (9)
On Instrumental Variable Regression for Deep Offline Policy Evaluation (2021) (9)
Particle Approximation of the Intensity Measures of a Spatial Branching Point Process Arising in Multitarget Tracking (2010) (9)
Continual Repeated Annealed Flow Transport Monte Carlo (2022) (9)
On-line Bayesian modelling and enhancement of speech signals (2000) (9)
Space alternating data augmentation: application to finite mixture of Gaussians and speaker recognition (2005) (9)
Dual Space Preconditioning for Gradient Descent (2019) (9)
Training Dynamics of Deep Networks using Stochastic Gradient Descent via Neural Tangent Kernel (2019) (9)
Bayesian nonparametric image segmentation using a generalized Swendsen-Wang algorithm (2016) (9)
An introduction to the theory and applications of simulation based computational methods in Bayesian signal processing (1998) (8)
Online sampling for parameter estimation in general state space models (2003) (8)
Sequential simulation-based estimation of jump Markov linear systems (2000) (8)
Bayesian segmentation of piecewise constant autoregressive processes using MCMC methods (1999) (8)
Fluctuations of interacting Markov chain Monte Carlo methods (2012) (8)
Bayesian blind marginal separation of convolutively mixed discrete sources (1998) (8)
NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform (2021) (8)
Scalable Monte Carlo inference for state-space models (2018) (8)
Recursive Monte Carlo algorithms for parameter estimation in general state space models (2001) (8)
Nonreversible Jump Algorithms for Bayesian Nested Model Selection (2019) (8)
Adaptive MAP multi-user detection for fading CDMA channels (2000) (8)
Particle Filter as A Controlled Markov Chain For On-Line Parameter Estimation in General State Space Models (2006) (7)
Exponential forgetting and geometric ergodicity in state-space models (2002) (7)
Network Consensus in the Wasserstein Metric Space of Probability Measures (2014) (7)
Bayesian estimation of filtered point processes using Markov chain Monte Carlo methods (1997) (7)
Bayesian deconvolution of cyclostationary processes based on point processes (1996) (7)
Sparsity-Promoting Bayesian Dynamic Linear Models (2012) (7)
Particle Markov Chain Monte Carlo for Multiple Change-point Problems (2009) (7)
Score-Based Diffusion meets Annealed Importance Sampling (2022) (7)
On PAC-Bayesian reconstruction guarantees for VAEs (2022) (7)
Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling (2017) (7)
Two time-scale stochastic approximation for constrained stochastic optimization and constrained Markov decision problems (2003) (7)
Optimal Filtering For Partially Observed Point Processes Using Trans-Dimensional Sequential Monte Carlo (2006) (7)
Non-stationary Bayesian modelling and enhancement of speech signals (1999) (6)
Bernoulli Race Particle Filters (2019) (6)
Joint target tracking and identification. Part II. Shape video computing (2005) (6)
Conformal Off-Policy Prediction in Contextual Bandits (2022) (6)
Variance reduction for Monte Carlo implementation of adaptive sensor management (2004) (6)
Adapting two-class support vector classification methods to many class problems (2005) (6)
Particle filter for tracking linear Gaussian target with nonlinear observations (2003) (6)
Bayesian estimation of instantaneous frequency (1996) (6)
Wide stochastic networks: Gaussian limit and PAC-Bayesian training (2021) (6)
Joint Bayesian detection and estimation of sinusoids embedded in noise (1998) (6)
COIN++: Neural Compression Across Modalities (2022) (6)
One-line Parameter Estimation in General State-Space Models using a Pseudo-Likelihood Approach (2012) (6)
Particle approximations of a class of branching distribution ﬂows arising in multi-target tracking (2010) (6)
Fluctuations of Interacting Markov Chain Monte Carlo Models (2008) (6)
Multivariate Stochastic Volatility with Co-Heteroscedasticity (2018) (6)
Bayesian Blind and Semi-Blind Equalization of Channels with Markov Inputs (2001) (6)
Metropolis-Hastings with Averaged Acceptance Ratios (2020) (5)
Joint target tracking and identification-Part I: sequential Monte Carlo model-based approaches (2005) (5)
Distributed Online Self-Localization and Tracking in Sensor Networks (2007) (5)
Online Variational Filtering and Parameter Learning (2021) (5)
Schr\"odinger Bridge Samplers. (2019) (5)
An Adaptive Subsampling Approach for MCMC Inference in Large Datasets (2014) (5)
Efficient particle filters for tracking manoeuvring targets in clutter (1999) (5)
Conditionally Gaussian PAC-Bayes (2021) (5)
Stability of Optimal Filter Higher-Order Derivatives (2018) (5)
Sequential sampling for dynamic environment maps (2006) (5)
Ensemble Rejection Sampling (2020) (5)
Joint Channel and Doppler Offset Estimation in Dynamic Cooperative Relay Networks (2014) (5)
Chained Generalisation Bounds (2022) (5)
Particle filtering for multi-target tracking using jump Markov systems (2004) (5)
Convergence of the equi-energy sampler (2007) (5)
Some discussions of D. Fearnhead and D. Prangle's Read Paper "Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation" (2012) (4)
Particle filtering for joint symbol and parameter estimation in DS spread spectrum systems (2003) (4)
Conditional Gaussian PAC-Bayes (2021) (4)
Sequential Monte Carlo & genetic particle models. Theory and practice (2012) (4)
Analyticity of Entropy Rates of Continuous-State Hidden Markov Models (2018) (4)
Bayesian Nonparametric Models on Decomposable Graphs (2009) (4)
Bias Mitigated Learning from Differentially Private Synthetic Data: A Cautionary Tale (2021) (4)
Optimal Estimation of Amplitude and Phase Modulated Signals (2001) (4)
Efficient stochastic maximum a posteriori estimation for harmonic signals (1998) (4)
Bayesian filtering for hidden Markov models via Monte Carlo methods (1998) (4)
Discussion on the paper by Brooks, Giudici and Roberts (2003) (4)
Inference and Learning for Active Sensing, Experimental Design and Control (2009) (4)
Categorical SDEs with Simplex Diffusion (2022) (4)
A Distributed Recursive Maximum Likelihood Implementation for Sensor Registration (2006) (4)
Robust Bayesian spectral analysis via MCMC sampling (1998) (4)
A New Class of Soft MIMO (2003) (4)
Marginal MAP estimation using Markov chain Monte Carlo (1999) (4)
Markov Chain Monte Carlo Methods (2007) (4)
Bayesian estimation of the variance of a jitter using MCMC (1996) (4)
A policy gradient method for SMDPs with application to call admission control (2002) (4)
State estimation of jump Markov linear systems via stochastic sampling algorithms (1998) (3)
ANNEALED IMPORTANCE SAMPLING MEETS SCORE MATCHING (2022) (3)
Special Issue on Particle Filtering in Signal Processing (2004) (3)
Sequential Bayesian wavelet denoising (1999) (3)
Online Parameter Estimation for Partially Observed Diffusions (2006) (3)
Simulation-based computational methods for Bayesian signal processing (1998) (3)
Particle filtering for non-stationary speech modelling and enhancement (2000) (3)
Invertible Flow Non Equilibrium sampling (2021) (3)
Stochastic algorithms for marginal MAP retrieval of sinusoids in non-Gaussian noise (2000) (3)
Distributed Self Localisation of Sensor Networks using Particle Methods (2006) (3)
A Particle Method for Solving Fredholm Equations of the First Kind (2020) (3)
Replica Conditional Sequential Monte Carlo (2019) (3)
Localised Generative Flows (2019) (3)
Asymptotic Properties of Recursive Particle Maximum Likelihood Estimation (2019) (3)
Melody Tracking Based on Sequential Bayesian Model (2011) (3)
Particle filters for demodulation of M-ary modulated signals in noisy fading communication channels (2000) (3)
Fixed-lag sequential Monte Carlo (2004) (3)
Simulation of the Annual Loss Distribution in Operational Risk Via Panjer Recursions and Volterra Integral Equations for Value at Risk and Expected Shortfall Estimation. (2017) (3)
Discussions on "Riemann manifold Langevin and Hamiltonian Monte Carlo methods" (2010) (3)
Spectral Diffusion Processes (2022) (3)
Semi-supervised learning scheme using Dirichlet process EM-algorithm (パターン認識・メディア理解) (2009) (3)
A particle filter to mitigate jamming for GPS navigation (2005) (3)
Fully Bayesian analysis of conditionally linear Gaussian state space models (1996) (3)
SE(3) diffusion model with application to protein backbone generation (2023) (2)
New Results - Interacting Markov chain Monte Carlo methods (2008) (2)
A simulation based algorithm for optimal quantization of hidden Markov models (2003) (2)
On the convergence of a two timescale stochastic optimisation algorithm for optimal observer trajectory planning (2005) (2)
An Empirical Study of Implicit Regularization in Deep Offline RL (2022) (2)
Riemannian Diffusion Schrödinger Bridge (2022) (2)
Particle Filters for Graphical Models (2006) (2)
A Bayesian approach to harmonic retrieval with clipped data (1999) (2)
From Denoising Diffusions to Denoising Markov Models (2022) (2)
Bias of Particle Approximations to Optimal Filter Derivative (2018) (2)
Exponential forgetting and geo-metric ergodicity in general state-space models (2002) (2)
An introduction to the theory and applications of simulation based computational methods in Bayesian (1998) (2)
Convergence properties of Bayesian evolutionary algorithms with population size greater than 1 (2001) (2)
Optimal filtering for partially observed point processes using trans-dimensional Monte Carlo (2006) (2)
Markov chain Monte Carlo methods for tracking a maneuvering target in clutter (1998) (2)
A PAC-Bayes bound for deterministic classifiers (2022) (2)
Lithological tomography with the correlated pseudo-marginal method (2021) (2)
Efficient simulated annealing algorithms for Bayesian parameter estimation (1998) (2)
RANDOM FINITE SETS AND SEQUENTIAL MULTI-TARGET TRA (2006) (1)
Blind marginal maximum a posteriori sequence estimation for finite impulse response channels (1998) (1)
A particle filtering technique for Jump Markov Systems (2002) (1)
Asymptotic Properties of Recursive Particle Maximum Likelihood Estimation (2021) (1)
EXACT SAMPLING USING BRANCHING PARTICLE SIMULATION (2012) (1)
Monte Carlo and Quasi-Monte Carlo Methods 2008 (2009) (1)
A new FA property based genetic algorithm for improving source and channel estimates (2004) (1)
Sharp propagation of chaos estimates for Feynmann - Kac particle models@@@Sharp propagation of chaos estimates for Feynmann - Kac particle models (2006) (1)
On-line changepoint detection and parameter estimation with application to genomic data (2011) (1)
Maximum Likelihood Learning of Energy-Based Models for Simulation-Based Inference (2022) (1)
A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs (2023) (1)
Solving Fredholm Integral Equations of the First Kind via Wasserstein Gradient Flows (2022) (1)
Sequential Inference and Learning (1998) (1)
On the use and misuse of particle ltering in digital communications (2002) (1)
Interacting Particle Markov Chain Monte Carlo - Supplementary Material (2016) (1)
A new class of interacting Markov chain Monte Carlo methods (2010) (1)
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC (2023) (1)
THE UNIVERSITY OF BRITISH COLUMBIA DEPARTMENT OF STATISTICS TECHNICAL REPORT # 236 On-line Changepoint Detection and Parameter Estimation for Genome-wide Transcript Analysis (2007) (1)
Importance Weighted Kernel Bayes' Rule (2022) (1)
Maximum a Posteriori Parameter Estimation for Hidden Markov Models (2000) (1)
Sequential Ba yesian kernel regression (2004) (1)
Perfect simulation for the Feynman-Kac law on the path space (2012) (1)
Stochastic algorithms for Bayesian model selection of AR processes (1998) (1)
Differentiable samplers for deep latent variable models (2023) (1)
Fixed-lag sequential Monte Carlo data association (2006) (1)
Bayesian models selection approaches to model selection (2001) (1)
Importance Weighting Approach in Kernel Bayes' Rule (2022) (0)
Learning Ordinary Differential Equations with the Line Integral Loss Function (2022) (0)
Joint Bayesian model selection and blind equalization of ISI channels (2005) (0)
Efficient estimation of likelihood ratios in state-space models–application to scalable exact approximations of MCMCs (2015) (0)
A Monte Carlo Algorithm for Optimal Quantization in Hidden Markov Models (2007) (0)
Discussions on the Read Paper by Girolami and Calderhead "Riemann manifold Langevin and Hamil- tonian Monte Carlo methods" read to the Soci- ety on October 13th, 2010 (2010) (0)
Exact Convergence Rates of the Neural Tangent Kernel in the Large Depth Limit (2019) (0)
On the usefulness of asymmetric acceptance ratio Metropolis-Hastings update (2015) (0)
A Gaussian mixture ensemble transform filter for vector observations (2013) (0)
Preface (2014) (0)
Robust Predictive Uncertainty for Neural Networks via Confidence Densities (2019) (0)
Supplementary Material to Bernoulli Race Particle Filters (2019) (0)
Maximum Likelihood Learning of Unnormalized Models for Simulation-Based Inference (2022) (0)
Particle Filtering in Digital Communications (2007) (0)
Conditional Simulation Using Diffusion Schrödinger Bridges (Supplementary Material) (2022) (0)
Simulated likelihood inference for stochastic volatility models using continuous particle filtering (2014) (0)
RADIAL BASIS FUNCTION REGRESSION USING TRANS-DIMENSIONAL SEQUENTIAL (2003) (0)
Blind multi-user detectors exploiting spatial diversity in DS-CDMA downlink (2003) (0)
Diffusion Schr\"odinger Bridge Matching (2023) (0)
Calibration and Filtering for Multi Factor Commodity Models with Seasonality: Incorporating Panel Data from Futures Contracts (2012) (0)
Sequential Monte Carlo methods: new tools for optimal filtering, system identifcation and control of non-linear and non-gaussian models (2006) (0)
L EARNING O PTIMAL C ONFORMAL C LASSIFIERS (2022) (0)
Editorial (2004) (0)
DISTRIBUTEDSELFLOCALISATIONOF SENSORNETWORKS USINGPARTICLE METHODS (2006) (0)
“ MCMC : Recent developments and new connections ” 30 March to 03 April 2020 organized (2020) (0)
MCMC : Recent developments and new connections ” September 14 to 25 , 2020 organized (2020) (0)
An adaptive sequential Monte Carlo method for approximate Bayesian computation (2011) (0)
A simulation based algorithm for optimal quantization in non-linear/non-Gaussian state-space models (2004) (0)
Riemannian Diffusion Schr\"odinger Bridge (2022) (0)
NON-LINEAR MARKOV CHAIN MONTE (2007) (0)
Turning off the “ self-destruction ” mechanism of a cell (2012) (0)
A Functional Central Limit Theorem for a Class of Interacting Markov Chain Monte Carlo Models (2017) (0)
Expectation-maximization algorithms for inference in Dirichlet processes mixture (2011) (0)
PR ] 1 A ug 2 01 8 Stability of Optimal Filter Higher-Order Derivatives (2018) (0)
Simulation-based Methods for Blind Maximum-likelihood Filter Identiication Simulation-based Methods for Blind Maximum-likelihood Filter Identiication (2008) (0)
Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving (2022) (0)
Sampling-based near-optimal MIMO demodulation algorithms (2003) (0)
neural compression workshop COIN : CO MPRESSION WITH I MPLICIT N EURAL REPRESENTATIONS (2021) (0)
Inference of geostatistical hyperparameters with the correlated pseudo-marginal method (2023) (0)
On-line non-stationary independent component analysis of Gaussian mixtures (2000) (0)
Bayesian deconvolution of poissonian point sources (1998) (0)
Causal Falsification of Digital Twins (2023) (0)
Melody Tracking Based on Sequential (2011) (0)
Distributed maximum likelihood for self-localization in sensor networks (2009) (0)
Diversity Assisted Blind Channel Estimation and Multiuser Detection for DS-CDMA Downlink with Multipath Channels (2016) (0)
Mitigating statistical bias within differentially private synthetic data (2021) (0)
ONLINEPARAMETER ESTIMATIONFOR PARTIALLYOBSERVEDDIFFUSIONS (2006) (0)
Denoising Diffusion Samplers (2023) (0)
Ranking in Contextual Multi-Armed Bandits (2022) (0)
Grouping Priors and the Bayesian Elastic Net Luke (2010) (0)
Generalisation under gradient descent via deterministic PAC-Bayes (2022) (0)
Sequential Monte Carlo for Marginal Optimisation Problems (2006) (0)
Replica Conditional Sequential Monte (2019) (0)
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics (2022) (0)
Monte Carlo Methods, Sequential† (2014) (0)

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