Víctor Elvira

102 papers A* 3A 2B 1C 3Misc 20Journal 60Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Differentiable interacting multiple model particle filtering. Signal Process. John-Joseph Brady, Yuhui Luo, Wenwu Wang, Víctor Elvira, Yunpeng Li
2026	J	`jnl`	Discrete diffusion samplers and bridges: Off-policy algorithms and applications in latent spaces. CoRR Arran Carter, Sanghyeok Choi, Kirill Tamogashev, Víctor Elvira, Nikolay Malkin
2026	J	`jnl`	Effective sample size approximations as entropy measures. CoRR Luca Martino, Víctor Elvira
2026	J	`jnl`	Signature-Kernel Based Evaluation Metrics for Robust Probabilistic and Tail-Event Forecasting. CoRR Benjamin R. Redhead, Thomas L. Lee, Peng Gu, Víctor Elvira, Amos J. Storkey
2025	J	`jnl`	A Divergence-Based Condition to Ensure Quantile Improvement in Black-Box Global Optimization. IEEE Trans. Evol. Comput. Thomas Guilmeau, Emilie Chouzenoux, Víctor Elvira
2025	J	`jnl`	A Proximal Newton Adaptive Importance Sampler. IEEE Signal Process. Lett. Víctor Elvira, Émilie Chouzenoux, Ömer Deniz Akyildiz
2025	B	`conf`	Dimensionality Reduction with Entropies from f-Divergences. MDAI Mateu Sbert, Min Chen, Jordi Poch, Miquel Feixas, Shuning Chen, Víctor Elvira
2025	J	`jnl`	Effective sample size approximations as entropy measures. Comput. Stat. Luca Martino, Víctor Elvira
2025	J	`jnl`	GraphGrad: Efficient Estimation of Sparse Polynomial Representations for General State-Space Models. IEEE Trans. Signal Process. Benjamin Cox, Émilie Chouzenoux, Víctor Elvira
2025	J	`jnl`	Hybrid Population Monte Carlo. IEEE Trans. Signal Process. Ali Mousavi, Víctor Elvira
2025	Misc	`conf`	Learning a Sparse Polynomial Approximation to the Transition Function of General State-Space Models. ICASSP Benjamin Cox, Émilie Chouzenoux, Víctor Elvira
2025	J	`jnl`	Learning state and proposal dynamics in state-space models using differentiable particle filters and neural networks. Signal Process. Benjamin Cox, Santiago Segarra, Víctor Elvira
2025	—	`conf`	Local Particle Filters: a Unifying Framework and Novel Parallelizable Extensions. CAMSAP Andrea Quintanilla, Víctor Elvira
2025	J	`jnl`	Multi-Marginal Flow Matching with Adversarially Learnt Interpolants. CoRR Oskar Kviman, Kirill Tamogashev, Nicola Branchini, Víctor Elvira, Jens Lagergren, Nikolay Malkin
2025	—	`conf`	Multiple Importance Sampling Optimization with Linear Equations. EUSIPCO Mateu Sbert, László Szirmay-Kalos, Víctor Elvira
2025	J	`jnl`	PyDPF: A Python Package for Differentiable Particle Filtering. CoRR John-Joseph Brady, Benjamin Cox, Víctor Elvira, Yunpeng Li
2025	J	`jnl`	Regularized Rényi Divergence Minimization through Bregman Proximal Gradient Algorithms. J. Mach. Learn. Res. Thomas Guilmeau, Emilie Chouzenoux, Víctor Elvira
2025	J	`jnl`	Reinforced sequential Monte Carlo for amortised sampling. CoRR Sanghyeok Choi, Sarthak Mittal, Víctor Elvira, Jinkyoo Park, Nikolay Malkin
2025	J	`jnl`	Scalable Expectation Estimation with Subtractive Mixture Models. CoRR Lena Zellinger, Nicola Branchini, Víctor Elvira, Antonio Vergari
2025	—	`conf`	State-Space Partitioning via Granger Causality for Local Particle Filters. EUSIPCO Andrea Quintanilla, Víctor Elvira
2025	—	`conf`	Towards Adaptive Self-Normalized Importance Samplers. SSP Nicola Branchini, Víctor Elvira
2025	J	`jnl`	Using Machine Learning on MRI Radiomics to Diagnose Parotid Tumours Before Comparing Performance with Radiologists: A Pilot Study. J. Imaging Inform. Medicine Samy Ammari, Arnaud Quillent, Víctor Elvira, François Bidault, César Ignacio García-Osorio, Dana M. Hartl, Corinne Balleyguier, Nathalie Lassau, Émilie Chouzenoux
2024	J	`jnl`	Bayesian Data Fusion With Shared Priors. IEEE Trans. Signal Process. Peng Wu, Tales Imbiriba, Víctor Elvira, Pau Closas
2024	J	`jnl`	Differentiable Interacting Multiple Model Particle Filtering. CoRR John-Joseph Brady, Yuhui Luo, Wenwu Wang, Víctor Elvira, Yunpeng Li
2024	A*	`conf`	Efficient Mixture Learning in Black-Box Variational Inference. ICML Alexandra Hotti, Oskar Kviman, Ricky Molén, Víctor Elvira, Jens Lagergren
2024	J	`jnl`	Efficient Mixture Learning in Black-Box Variational Inference. CoRR Alexandra Hotti, Oskar Kviman, Ricky Molén, Víctor Elvira, Jens Lagergren
2024	Misc	`conf`	End-to-End Learning of Gaussian Mixture Proposals Using Differentiable Particle Filters and Neural Networks. ICASSP Benjamin Cox, Sara Pérez-Vieites, Nicolas Zilberstein, Martin Sevilla, Santiago Segarra, Víctor Elvira
2024	Misc	`conf`	Graphical Inference in Non-Markovian Linear-Gaussian State-Space Models. ICASSP Emilie Chouzenoux, Víctor Elvira
2024	J	`jnl`	Hierarchical Average Fusion With GM-PHD Filters Against FDI and DoS Attacks. IEEE Signal Process. Lett. Hao Yang, Tiancheng Li, Junkun Yan, Víctor Elvira
2024	J	`jnl`	Information Fusion via Importance Sampling. IEEE Trans. Signal Inf. Process. over Networks Augustin-Alexandru Saucan, Víctor Elvira, Pramod K. Varshney, Moe Z. Win
2024	C	`conf`	Regime Learning for Differentiable Particle Filters. FUSION John-Joseph Brady, Yuhui Luo, Wenwu Wang, Víctor Elvira, Yunpeng Li
2024	A	`conf`	Variational Resampling. AISTATS Oskar Kviman, Nicola Branchini, Víctor Elvira, Jens Lagergren
2024	C	`conf`	WALGREEN: Web Based Platform for Soil Organic Carbon Inference Applications. IGARSS José Manuel Aroca, José-Francisco Díez-Pastor, Pedro Latorre-Carmona, Antonio Canepa-Oneto, Juan Carlos Rad, Gustau Camps-Valls, Víctor Elvira, César García-Osorio
2023	J	`jnl`	A point mass proposal method for Bayesian state-space model fitting. Stat. Comput. Mary Llewellyn, Ruth King, Víctor Elvira, Gordon Ross
2023	Misc	`conf`	Adaptive Gaussian Nested Filter for Parameter Estimation and State Tracking in Dynamical Systems. ICASSP Sara Pérez-Vieites, Víctor Elvira
2023	Misc	`conf`	Adaptive Simulated Annealing Through Alternating Rényi Divergence Minimization. ICASSP Thomas Guilmeau, Emilie Chouzenoux, Víctor Elvira
2023	Misc	`conf`	An Augmented Gaussian Sum Filter through a mixture Decomposition. ICASSP Kostas Tsampourakis, Víctor Elvira
2023	A*	`conf`	Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational Autoencoders. ICML Oskar Kviman, Ricky Molén, Alexandra Hotti, Semih Kurt, Víctor Elvira, Jens Lagergren
2023	—	`conf`	Differentiable Bootstrap Particle Filters for Regime-Switching Models. SSP Wenhan Li, Xiongjie Chen, Wenwu Wang, Víctor Elvira, Yunpeng Li
2023	J	`jnl`	Differentiable Bootstrap Particle Filters for Regime-Switching Models. CoRR Wenhan Li, Xiongjie Chen, Wenwu Wang, Víctor Elvira, Yunpeng Li
2023	J	`jnl`	Efficient bayes inference in neural networks through adaptive importance sampling. J. Frankl. Inst. Yunshi Huang, Emilie Chouzenoux, Víctor Elvira, Jean-Christophe Pesquet
2023	J	`jnl`	Gradient-based adaptive importance samplers. J. Frankl. Inst. Víctor Elvira, Emilie Chouzenoux, Ömer Deniz Akyildiz, Luca Martino
2023	Misc	`conf`	Graphit: Iterative Reweighted ℓ1 Algorithm for Sparse Graph Inference in State-Space Models. ICASSP Emilie Chouzenoux, Víctor Elvira
2023	J	`jnl`	Graphs in State-Space Models for Granger Causality in Climate Science. CoRR Víctor Elvira, Emilie Chouzenoux, Jordi Cerdà, Gustau Camps-Valls
2023	—	`conf`	Redistribution Networks for Resampling. CAMSAP Michael Lunglmayr, Víctor Elvira
2023	J	`jnl`	Sparse Bayesian Estimation of Parameters in Linear-Gaussian State-Space Models. IEEE Trans. Signal Process. Benjamin Cox, Víctor Elvira
2023	Misc	`conf`	State and Dynamics Estimation with the Kalman-Langevin filter. ACSSC Martin Sevilla, Nicolas Zilberstein, Benjamin Cox, Sara Pérez-Vieites, Víctor Elvira, Santiago Segarra
2022	Misc	`conf`	Approximating The Likelihood Ratio in Linear-Gaussian State-Space Models for Change Detection. ICASSP Kostas Tsampourakis, Víctor Elvira
2022	J	`jnl`	Generalizing the Balance Heuristic Estimator in Multiple Importance Sampling. Entropy Mateu Sbert, Víctor Elvira
2022	J	`jnl`	Graphical Inference in Linear-Gaussian State-Space Models. IEEE Trans. Signal Process. Víctor Elvira, Emilie Chouzenoux
2022	J	`jnl`	Hamiltonian Adaptive Importance Sampling. CoRR Ali Mousavi, Reza Monsefi, Víctor Elvira
2022	J	`jnl`	Learning with MISELBO: The Mixture Cookbook. CoRR Oskar Kviman, Ricky Molén, Alexandra Hotti, Semih Kurt, Víctor Elvira, Jens Lagergren
2022	J	`jnl`	Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations. CoRR Oskar Kviman, Harald Melin, Hazal Koptagel, Víctor Elvira, Jens Lagergren
2022	J	`jnl`	Optimized Population Monte Carlo. IEEE Trans. Signal Process. Víctor Elvira, Emilie Chouzenoux
2022	—	`conf`	Parameter Estimation in Sparse Linear-Gaussian State-Space Models via Reversible Jump Markov Chain Monte Carlo. EUSIPCO Benjamin Cox, Víctor Elvira
2022	Misc	`conf`	Proximal-Based Adaptive Simulated Annealing for Global Optimization. ICASSP Thomas Guilmeau, Emilie Chouzenoux, Víctor Elvira
2021	—	`conf`	A Nearest Neighbors Quadrature for Posterior Approximation via Adaptive Sequential Design. SSP Fernando Llorente, Luca Martino, Víctor Elvira, David Delgado
2021	J	`jnl`	An Efficient Sampling Scheme for the Eigenvalues of Dual Wishart Matrices. IEEE Signal Process. Lett. Ignacio Santamaría, Víctor Elvira
2021	J	`jnl`	Compressed Monte Carlo with application in particle filtering. CoRR Luca Martino, Víctor Elvira
2021	J	`jnl`	Compressed Monte Carlo with application in particle filtering. Inf. Sci. Luca Martino, Víctor Elvira
2021	J	`jnl`	Compressed Particle Methods for Expensive Models With Application in Astronomy and Remote Sensing. IEEE Trans. Aerosp. Electron. Syst. Luca Martino, Víctor Elvira, Javier López-Santiago, Gustau Camps-Valls
2021	J	`jnl`	Compressed particle methods for expensive models with application in Astronomy and Remote Sensing. CoRR Luca Martino, Víctor Elvira, Javier López-Santiago, Gustau Camps-Valls
2021	J	`jnl`	Hamiltonian Adaptive Importance Sampling. IEEE Signal Process. Lett. Ali Mousavi, Reza Monsefi, Víctor Elvira
2021	C	`conf`	Importance Gauss-Hermite Gaussian Filter for Models with Non-Additive Non-Gaussian Noises. FUSION Ondrej Straka, Jindrich Duník, Víctor Elvira
2021	J	`jnl`	Importance Gaussian Quadrature. IEEE Trans. Signal Process. Víctor Elvira, Luca Martino, Pau Closas
2021	J	`jnl`	Multiple Importance Sampling for Symbol Error Rate Estimation of Maximum-Likelihood Detectors in MIMO Channels. IEEE Trans. Signal Process. Víctor Elvira, Ignacio Santamaría
2021	J	`jnl`	Nearly Consistent Finite Particle Estimates in Streaming Importance Sampling. IEEE Trans. Signal Process. Alec Koppel, Amrit Singh Bedi, Brian M. Sadler, Víctor Elvira
2021	J	`jnl`	On the performance of particle filters with adaptive number of particles. Stat. Comput. Víctor Elvira, Joaquín Míguez, Petar M. Djuric
2021	A	`conf`	Optimized auxiliary particle filters: adapting mixture proposals via convex optimization. UAI Nicola Branchini, Víctor Elvira
2021	J	`jnl`	Probabilistic Modeling and Inference for Sequential Space-Varying Blur Identification. IEEE Trans. Computational Imaging Yunshi Huang, Emilie Chouzenoux, Víctor Elvira
2021	J	`jnl`	Recurrent dictionary learning for state-space models with an application in stock forecasting. Neurocomputing Shalini Sharma, Víctor Elvira, Emilie Chouzenoux, Angshul Majumdar
2021	—	`conf`	Simulated Annealing: a Review and a New Scheme. SSP Thomas Guilmeau, Emilie Chouzenoux, Víctor Elvira
2021	J	`jnl`	Stochastic Order and Generalized Weighted Mean Invariance. Entropy Mateu Sbert, Jordi Poch, Shuning Chen, Víctor Elvira
2021	A*	`conf`	Would Your Tweet Invoke Hate on the Fly? Forecasting Hate Intensity of Reply Threads on Twitter. KDD Snehil Dahiya, Shalini Sharma, Dhruv Sahnan, Vasu Goel, Emilie Chouzenoux, Víctor Elvira, Angshul Majumdar, Anil Bandhakavi, Tanmoy Chakraborty
2020	J	`jnl`	A survey of Monte Carlo methods for parameter estimation. EURASIP J. Adv. Signal Process. David Luengo, Luca Martino, Mónica F. Bugallo, Víctor Elvira, Simo Särkkä
2020	J	`jnl`	Adaptive quadrature schemes for Bayesian inference via active learning. CoRR Fernando Llorente, Luca Martino, Víctor Elvira, David Delgado, Javier López-Santiago
2020	Misc	`conf`	Graphem: EM Algorithm for Blind Kalman Filtering Under Graphical Sparsity Constraints. ICASSP Emilie Chouzenoux, Víctor Elvira
2020	Misc	`conf`	Particle Group Metropolis Methods for Tracking the Leaf Area Index. ICASSP Luca Martino, Víctor Elvira, Gustau Camps-Valls
2019	J	`jnl`	A Probabilistic Incremental Proximal Gradient Method. IEEE Signal Process. Lett. Ömer Deniz Akyildiz, Emilie Chouzenoux, Víctor Elvira, Joaquín Míguez
2019	Misc	`conf`	Compressed Streaming Importance Sampling for Efficient Representations of Localization Distributions. ACSSC Amrit Singh Bedi, Alec Koppel, Brian M. Sadler, Víctor Elvira
2019	—	`conf`	Efficient Adaptive Multiple Importance Sampling. EUSIPCO Yousef El-Laham, Luca Martino, Víctor Elvira, Mónica F. Bugallo
2019	Misc	`conf`	Efficient SER Estimation for MIMO Detectors via Importance Sampling Schemes. ACSSC Víctor Elvira, Ignacio Santamaría
2019	Misc	`conf`	Langevin-based Strategy for Efficient Proposal Adaptation in Population Monte Carlo. ICASSP Víctor Elvira, Emilie Chouzenoux
2019	J	`jnl`	Multiple Importance Sampling for Efficient Symbol Error Rate Estimation. CoRR Víctor Elvira, Ignacio Santamaría
2019	—	`conf`	Particle Filtering for Online Space-Varying Blur Identification. CAMSAP Yunshi Huang, Emilie Chouzenoux, Víctor Elvira
2019	—	`conf`	Recursive Shrinkage Covariance Learning in Adaptive Importance Sampling. CAMSAP Yousef El-Laham, Víctor Elvira, Mónica F. Bugallo
2018	J	`jnl`	Efficient linear fusion of partial estimators. Digit. Signal Process. David Luengo, Luca Martino, Víctor Elvira, Mónica F. Bugallo
2018	J	`jnl`	Group Importance Sampling for particle filtering and MCMC. Digit. Signal Process. Luca Martino, Víctor Elvira, Gustau Camps-Valls
2018	J	`jnl`	Multiple importance sampling characterization by weighted mean invariance. Vis. Comput. Mateu Sbert, Vlastimil Havran, László Szirmay-Kalos, Víctor Elvira
2018	J	`jnl`	The Recycling Gibbs sampler for efficient learning. Digit. Signal Process. Luca Martino, Víctor Elvira, Gustau Camps-Valls
2017	J	`jnl`	Cooperative parallel particle filters for online model selection and applications to urban mobility. Digit. Signal Process. Luca Martino, Jesse Read, Víctor Elvira, Francisco Louzada
2017	J	`jnl`	Effective sample size for importance sampling based on discrepancy measures. Signal Process. Luca Martino, Víctor Elvira, Francisco Louzada
2017	Misc	`conf`	Estimation of real valued impulse responses based on noisy magnitude and phase measurements. ACSSC Oliver Lang, Víctor Elvira, Mario Huemer
2017	J	`jnl`	Improving population Monte Carlo: Alternative weighting and resampling schemes. Signal Process. Víctor Elvira, Luca Martino, David Luengo, Mónica F. Bugallo
2016	J	`jnl`	On the Relationship between Online Gaussian Process Regression and Kernel Least Mean Squares Algorithms. CoRR Steven Van Vaerenbergh, Jesus Fernandez-Bes, Víctor Elvira
2016	J	`jnl`	Orthogonal parallel MCMC methods for sampling and optimization. Digit. Signal Process. Luca Martino, Víctor Elvira, David Luengo, Jukka Corander, Francisco Louzada
2015	J	`jnl`	A Probabilistic Least-Mean-Squares Filter. CoRR Jesus Fernandez-Bes, Víctor Elvira, Steven Van Vaerenbergh
2015	Misc	`conf`	A gradient adaptive population importance sampler. ICASSP Víctor Elvira, Luca Martino, David Luengo, Jukka Corander
2015	Misc	`conf`	A probabilistic least-mean-squares filter. ICASSP Jesus Fernandez-Bes, Víctor Elvira, Steven Van Vaerenbergh
2015	—	`conf`	Causality Analysis of Atrial Fibrillation Electrograms. CinC David Luengo, Gonzalo R. Ríos-Muñoz, Víctor Elvira
2015	Misc	`conf`	Efficient linear combination of partial Monte Carlo estimators. ICASSP David Luengo, Luca Martino, Víctor Elvira, Mónica F. Bugallo
2015	Misc	`conf`	Smelly parallel MCMC chains. ICASSP Luca Martino, Víctor Elvira, David Luengo, Antonio Artés-Rodríguez, Jukka Corander