Publications

All my publications are open access and can be found either below or in my Google Scholar profile.

Journal papers

  1. T. Guilmeau, E. Chouzenoux, and V. Elvira, "Regularized R\'enyi divergence minimization through Bregman proximal gradient algorithms" (to appear in), Journal of Machine Learning Research, 2025.
  2. B. Cox, E. Chouxenoux, V. Elvira, "GraphGrad: Efficient Estimation of Sparse Polynomial Representations for General State-Space Models", IEEE Transactions on Signal Processing (to appear in), 2025.
  3. V. Elvira, E. Chouzenoux, O. D. Akyildiz, "A Proximal Newton Adaptive Importance Sampler", IEEE Signal Processing Letters (to appear in), 2025.
  4. B. Cox, S. Segarra, V. Elvira, "Learning state and proposal dynamics in state-space models using differentiable particle filters and neural networks", Signal Processing (to appear in), 2025. [arXiv]
  5. E. Chouzenoux and V. Elvira, "Sparse Graphical Linear Dynamical Systems", Journal of Machine Learning Research, Vol. 25, No. 223, pp. 1-53, 2024. [arXiv]
  6. T. Guilmeau, E. Chouzenoux, and V. Elvira, "A Divergence-Based Condition to Ensure Quantile Improvement in Black-Box Global Optimization", IEEE Transactions on Evolutionary Computation (to appear in), 2024. [arXiv]
  7. S. Ammari, A. Quillent, E. Ouraou, M. Elhaik, V. Elvira, F. Bidault, D. M. Hartl, N. Lassau, C. Balleyguier, E. Chouzenoux, "Using machine learning on MRI radiomics to diagnose parotid tumours", Journal of Imaging Informatics in Medicine (to appear in), 2024.
  8. S. Orujov, A. Poterie, V. Elvira, F. Septier, "VS-LTGARCHX: A Flexible Subset Selection Approach for Estimation of log-TGARCHX Models and Its Application to BTC Markets", Journal of Time Series Econometrics (to appear in), 2024.
  9. T. Guilmeau, E. Chouzenoux, and V. Elvira, "On variational inference and maximum likelihood estimation with the λ-exponential family", Journal of Foundations in Data Science, vol. 6, issue 1, pp. 85-123. 2024. [arXiv]
  10. N. Branchini and V. Elvira "An adaptive mixture view of particle filters", to appear in Journal of Foundations in Data Science, 2024.
  11. R. Akeresola, A. Butler, E. Jones, R. King, V. Elvira, J. Black, and G. Robertson, "Validating hidden Markov models for seabird behavioural inference", Ecology and Evolution, vol. 14, issue 3, e11116, 2024.
  12. H. Yang, T. Li, J Yan, V. Elvira "Hierarchical Average Fusion with GM-PHD Filters Against FDI and DoS Attacks", IEEE Signal Processing Letters, vol. 31, pp. 934-938, 2024.
  13. P. Wu, T. Imbiriba, V. Elvira, and P. Closas, "Bayesian data fusion with shared priors", IEEE Transactions on Signal Processing, vol. 72, pp. 275-288, 2024. [arXiv]
  14. R. Mukerjee, V. Elvira, "Variance Analysis of Multiple Importance Sampling Schemes", Statistics, vol. 57, no. 6, 1392–1401. 2024. [arXiv]
  15. V. Elvira, E. Chouzenoux, O. D. Akyildiz, L. Martino, "Gradient-based adaptive importance samplers", Journal of the Franklin Institute, vol. 360, issue 13, pp. 9490-9514, 2023. [arXiv]
  16. Y. Huang, E. Chouzenoux, V. Elvira, J.-C. Pesquet, "Efficient Bayes Inference in Neural Networks through Adaptive Importance Sampling", Journal of the Franklin Institute, vol. 360, issue 16, pp. 12125-12149, 2023. [arXiv]
  17. A. A. Saucan, V. Elvira, P. K. Varshney, and M. Z. Win, "Information Fusion via Importance Sampling", IEEE Transactions on Signal and Information Processing over Networks, vol. 10, pp. 376-389, 2023.
  18. M. Llewellyn, R. King, V. Elvira, G. Ross, "A Point Mass Proposal Method for Bayesian State-Space Model Fitting", Statistics and Computing, vol. 33, number 111, 2023. [arXiv]
  19. B. Cox, V. Elvira, "Sparse Bayesian Estimation of Parameters in Linear-Gaussian State-Space Models", IEEE Transactions on Signal Processing, vol. 71, pp. 1922-1937, 2023.
  20. K. Rosen, C. Angeles-Camacho, V. Elvira, and S. T. Guillén-Burguete, "Intra-hour photovoltaic forecasting through a time-varying Markov switching model", Energy, vol. 278, part B, pp. 127952, 2023.
  21. R. King, B. Sarzo, and V. Elvira, "When Ecological Individual Heterogeneity Models and Large Data Collide: An Importance Sampling Approach", Annals of Applied Statistics, vol.17, no. 4, 2023. [arXiv]
  22. K. Newman, R. King, V. Elvira, P. de Valpine, R. S. McCrea, and B. J. T. Morgan, "State-space Models for for Ecological Time Series Data: Practical Model-fitting", Ecology and Evolution, vol. 1, issue 1, p. 26-42, 2023.
  23. A. Sanchez-Sanz, S. Garcia-Martin, J. Sabin-Munoz, I. Moreno-Torres, V. Elvira, F. Al-Shahrour, A. Garcia-Grande, E. Ramil, O. Rodriguez-De la Fuente, B. Brea-Alvarez, Ruth Garcia-Hernández, Antonio Garcia-Merino, Antonio J. Sanchez-Lopez, "Dimethyl fumarate-related immune and transcriptional signature is associated with clinical response in multiple sclerosis-treated patients", Frontiers in Immunology, vol. 14, 2023.
  24. S. Sharma, A. Majumdar, E. Chouzenoux, V. Elvira, "Deep state space model for predicting cryptocurrency price", Information Sciences, vol. 618, pp. 417-433, November, 2022.
  25. M. Agarwal, D. Vats, V. Elvira, "A principled stopping rule for importance sampling", Electronic Journal of Statistics, vol. 16, issue 2, p. 5570 - 5590, 2022. [arXiv]
  26. V. Elvira, É. Chouzenoux, "Graphical Inference in Linear-Gaussian State-Space Models", IEEE Transactions on Signal Processing, vol. 70, pp. 4757-4771, 2022. [arXiv]
  27. V. Elvira, É. Chouzenoux, "Optimized Population Monte Carlo", IEEE Transactions on Signal Processing, vol. 70, pp. 2489 - 2501, 2022. [arXiv]
  28. V. Elvira, L. Martino, C. P. Robert, "Rethinking the Effective Sample Size", International Statistical Review, vol. 90, issue 3, p. 525-550, 2022. [arXiv]
  29. F. Llorente, E. Curbelo, L. Martino, V. Elvira, D. Delgado, "MCMC-driven importance samplers", Applied Mathematical Modelling, vol. 111, pp. 310-331, 2022. [arXiv]
  30. C. Liu, K. Di, T. Li, and V. Elvira, "A sensor selection approach to maneuvering target tracking based on trajectory function of time", EURASIP Journal Advances in Signal Processing, vol. 2022, no 72, p. 1-14, 2022.
  31. M. Sbert, V. Elvira, "Generalizing the Balance Heuristic Estimator in Multiple Importance Sampling", Entropy, vol. 24, issue 2, 191, 2022. [arXiv]
  32. V. Elvira, J. Miguez, P. M. Djuric, "On the performance of particle filters with adaptive number of particles", Statistics and Computing, vol. 31, no. 6, pp. 1-18, 2021. [arXiv]
  33. I. Santamaría, V. Elvira "An Efficient Sampling Scheme for the Eigenvalues of Dual Wishart Matrices", IEEE Signal Processing Letters, vol. 28, pp. 2177-2181, March, 2021.
  34. A. Koppel, A. S. Bedi, B. M. Sadler, V. Elvira, "Nearly Consistent Finite Particle Estimates in Streaming Importance Sampling", IEEE Transactions on Signal Processing, vol. 69, pp. 6401-6415, 2021. [arXiv]
  35. Y. Huang, É. Chouzenoux, and V. Elvira, "Probabilistic modeling and inference for sequential space-varying blur identification", IEEE Transactions on Computational Imaging, vol. 7, pp. 531-546, 2021.
  36. M. Sbert, J. Poch, S. Chen, V. Elvira , "Stochastic order and generalized weighted mean invariance", Entropy, vol. 23, issue 6, pp 1–19, 2021. [pdf] 
  37. V. Elvira, I. Santarmaría, "Multiple Importance Sampling for Symbol Error Rate Estimation of Maximum-Likelihood Detectors in MIMO Channels'', IEEE Transactions on Signal Processing, vol. 69, pp. 1200 - 1212, January, 2021. [pdf] 
  38. V. Elvira, P. Closas, L. Martino, "Importance Gaussian Quadrature'', IEEE Transactions on Signal Processing, vol. 69, pp. 474 - 488, January, 2021. [arXiv] [pdf] 
  39. S. Sharma, V. Elvira, A. Majumdar, E. Chouzenoux, "Recurrent Dictionary Learning for State-Space Models with an Application in Stock Forecasting", Neurocomputing, vol. 450, pp. 1-13, 2021. [pdf] 
  40. L. Martino, V. Elvira, J. López-Santiago and G. Camps-Valls, "Compressed particle methods for expensive models with application in Astronomy and Remote Sensing", IEEE Transactions on Aerospace and Electronic Systems, vol. 57, issue 5, pp. 2607-2621, 2021. [pdf] 
  41. A. Mousavi, R. Monsefi, and V. Elvira, "Hamiltonian Adaptive Importance Sampling", IEEE Signal Processing Letters, vol. 28, pp. 713-717, March, 2021.
  42. I. Moreno-Torres, V. Meca, L. Costa- Frossard, C. Oreja-Guevara, C. Aguirre, E. Suarez, M. Gomez, L. Borrega, J. Sabin, Y, Aladro, A. Carcamo, E. Rodriguez, J. Cuello, E. Monreal, S. Sainz, F. Perez, F. Valenzuela, C. Lopez de Silanes, L. Casanova, M. Martinez, M. Blasco, A. Orviz, L. Villar- Guimerans, G. Fernandez-Dono, V. Elvira, C. Santiuste, M. Espino, Jose García, "Risk and outcomes of COVID-19 in patients with multiple sclearosis", European Journal of Neurology, vol. 28, issue 11, pp. 3384–3395, 2021.
  43. F. Llorente, L. Martino, V. Elvira, D. Delgado, J. Lopez-Santiago, "Adaptive quadrature schemes for Bayesian inference via active learning'', IEEE Access, vol 8, p. 208462 - 208483, 2020. [pdf] 
  44. L. Martino, V. Elvira, "Compressed Monte Carlo with application in particle filtering", Information Sciences", vol. 553, pp. 331-352, 2021. [pdf] 
  45. S. Sharma, A. Majumdar, V. Elvira, E. Chouzenoux, "Blind Kalman Filtering for Short-term Load Forecasting", IEEE Transactions on Power Systems, vol. 35, no 6, p. 4916-4919, 2020. [pdf] 
  46. V. Elvira, L. Martino, "Advances in Importance Sampling", Wiley StatsRef: Statistics Reference Online, pp. 1-14, 2021. [pdf] 
  47. D. Luengo, L. Martino, M. F. Bugallo, V. Elvira, S. Sarkka, "A Survey of Monte Carlo Methods for Parameter Estimation", EURASIP Journal Advances in Signal Processing, vol. 2020, no 1, p. 1-62, 2020. [pdf] 
  48. V. Elvira, L. Martino, M. F. Bugallo, and P. M. Djuric, "Elucidating the auxiliary particle filter via multiple importance sampling",vol. 36, no 6, p. 145-152, IEEE Signal Processing Magazine, 2019. [pdf] 
  49. V. Elvira, L. Martino, D. Luengo, and M. F. Bugallo, "Generalized Multiple Importance Sampling", Statistical Science, vol. 34, no. 1, pp. 129-155, 2019. [arXiv] [pdf] 
  50. V. Elvira, I. Santamaría, "Multiple Importance Sampling for Efficient Symbol Error Rate Estimation", IEEE Signal Processing Letters, vol. 26, no. 3, pp. 420-424, March, 2019. [arXiv] [pdf] 
  51. Ö. D. Akyildiz, É. Chouzenoux, V. Elvira, J. Míguez, "A probabilistic incremental proximal gradient method", IEEE Signal Processing Letters, vol. 26, no. 6, pp. 1257-1261, July, 2019. [arXiv]
  52. C. P. Robert, V. Elvira, N. Tawn, C. Wu, "Accelerating MCMC Algorithms", WIREs Computational Statistics, vol. 10, no. 5, e1435, 2018. [arXiv] [pdf] 
  53. L. Martino, V. Elvira, G. Camps-Valls, "Group Importance Sampling for Particle Filtering and MCMC", Digital Signal Processing, vol. 82, pp. 133-151, 2018. [arXiv]
  54. Y. El-Laham, V. Elvira, M. F. Bugallo, "Robust Covariance Adaptation in Adaptive Importance Sampling", IEEE Signal Processing Letters, vol. 25, no. 7, pp. 1049-1053, July, 2018. [arXiv] [pdf] 
  55. T. Li, V. Elvira, H. Fan, and J. M. Corchado, "Local Diffusion based Distributed SMC-PHD Filtering Using Sensors with Limited Sensing Range", IEEE Sensors, vol. 19, no. 4, pp. 1580-1589, February, 2019.
  56. I. Moreno-Torres, C. González, M. Marconi, A. García, L. Rodriguez, V. Elvira, E. Ramil, L. Campos, R. García, F. Al-Shahrour, C. Fustero, A. Sánchez, A. García-Merino, A. Sánchez-López, "Immunophenotype and Transcriptome Profile of Patients with Multiple Sclerosis Treated with Fingolimod. Setting Up a Model for Prediction of Response in a 2-Year Translational Study", Frontiers in Immunology, vol. 9, no. 1693, 2018.
  57. D. Luengo, G. Ríos-Muñoz, V. Elvira, C. Sánchez, A. Artés-Rodríguez, "Hierarchical Algorithms for Causality Retrieval in Atrial Fibrillation Intracavitary Electrograms", IEEE Journal of Biomedical and Health Informatics, vol. 12, no. 1, pp. 143-155, January, 2019.
  58. M. Sbert, H. Havran, L. Szirmay-Kalos, V. Elvira, "Multiple Importance Sampling Characterization by Weighted Mean Invariance”, Visual Computer, vol. 34, issue 6–8, pp 843–852, June 2018.
  59. L. Martino, V. Elvira, G. Camps-Valls, "The Recycling Gibbs Sampler for Efficient Learning", Digital Signal Processing, vol. 74, pp. 1-13, March, 2018. [arXiv] [pdf] 
  60. D. Luengo, L. Martino, V. Elvira, M. F. Bugallo, "Efficient Linear Fusion of Partial Estimators", Digital Signal Processing, vol. 78, pp. 265-283, July, 2018. [pdf] 
  61. V. Elvira, J. Míguez, and P. M. Djuric, "Adapting the Number of Particles in Sequential Monte Carlo Methods through an Online Scheme for Convergence Assessment", IEEE Transactions on Signal Processing, vol. 65, no. 7, pp. 1781-1794, April, 2017. [arXiv]
  62. M. F. Bugallo, V. Elvira, L. Martino, D. Luengo, J. Míguez, and P. M. Djuric, "Adaptive Importance Sampling: The Past, the Present, and the Future", IEEE Signal Processing Magazine, vol. 34, no. 4, pp. 60-79, July, 2017. [pdf] 
  63. V. Elvira, L. Martino, D. Luengo, and M. F. Bugallo, "Improving Population Monte Carlo: Alternative Weighting and Resampling Schemes", Signal Processing, vol. 131, pp. 77-91, February, 2017. [arXiv] [pdf] 
  64. L. Martino, V. Elvira, and F. Louzada, "Effective Sample Size for Importance Sampling Based on the Discrepancy Measures", Signal Processing, vol. 131, pp. 386-401, February, 2017. [arXiv] [pdf] 
  65. L. Martino, J. Read, V. Elvira, and F. Louzada, "Cooperative Parallel Particle Filters for On-line Model Selection and Applications to Urban Mobility", Digital Signal Processing, vol. 60, pp. 172–185, January, 2017. [arXiv] [pdf] 
  66. L. Martino, V. Elvira, D. Luengo, and J. Corander, "Layered Adaptive Importance Sampling", Statistics and Computing, vol. 27, no. 3, pp. 599-623, May. 2017. [arXiv] [pdf] 
  67. L. Martino, V. Elvira, "Metropolis Hastings", Wiley StatsRef: Statistics Reference Online, 2017. [arXiv] [pdf] 
  68. V. Elvira, L. Martino, D. Luengo, and M. F. Bugallo, "Heretical Mutiple Importance Sampling", IEEE Signal Processing Letters, vol. 23, no. 10, pp. 1474-1478, October, 2016. [arXiv] [pdf] 
  69. L. Martino, V. Elvira, D. Luengo, and J. Corander, and F. Louzada "Orthogonal parallel MCMC methods for sampling and optimization", Digital Signal Processing, vol. 58, pp. 64-84, November, 2016. [arXiv] [pdf] 
  70. V. Elvira, L. Martino, D. Luengo, and M. F. Bugallo, "Efficient Multiple Importance Sampling Estimators", IEEE Signal Processing Letters, vol. 22, no. 10, pp. 1757-1761, March, 2015. [arXiv] [pdf] 
  71. L. Martino, V. Elvira, D. Luengo, and J. Corander, "An Adaptive Population Importance Sampler: Learning from the Uncertanity", IEEE Transactions on Signal Processing, vol. 63, no. 16, pp. 4422-4437, August, 2015. [pdf] 
  72. V. Elvira, and J. Vía, "Analog antenna combining in transmit correlated channels: Transceiver design and performance evaluation", Signal Processing, vol. 92, no. 3, pp. 757-766, March, 2012. [pdf] 
  73. Z. Stamenkovic, K. Tittelbach-Helmrich, M. Krstic, J. Ibáñez, V. Elvira, and I. Santamaría, "MAC and Baseband Processors for RF-MIMO WLAN", EURASIP Journal on Wireless Communications and Networking, December, 2011. [pdf] 
  74. J. Vía, I. Santamaría, V. Elvira, and R. Eickhoff, "A General Criterion for Analog Tx-Rx Beamforming under OFDM Transmissions", IEEE Transactions on Signal Processing, vol. 58, no. 4, pp. 2155-2167, April, 2010. [pdf] 

Refereed conference papers

  1. S. Helal, V. Elvira, "Subset adaptive importance sampling for multi-failure-region estimation", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2025), Hyderabad, India, April, 2025.
  2. B. Cox, E. Chouzenoux, V. Elvira, "Learning a sparse polynomial approximation to the transition function of general state-space models", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2025), Hyderabad, India, April, 2025.
  3. A. Hotti, O. Kviman, R. Molen, V. Elvira, J. Lagergren, "Efficient Mixture Learning in Black-Box Variational Inference", 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, July, 2024.
  4. J. J. Brady, Y. Luo, W. Wang, V. Elvira, and Y. Li, "Regime Learning for Differentiable Particle Filters", 27th International Conference on Information Fusion, Venice, Italy, 2024.
  5. J. M. Aroca, J. F. Diez Pastor, P. Latorre-Carmona, A. Canepa-Oneto, J. Carlos Rad, G. Camps-Valls, V. Elvira, C. Garcia-Osorio, "Wallgreen: web based platform for soil organic carbon inference applications", IEEE International Geoscience and Remote Sensing Symposium, 2024.
  6. T. Guilmeau, N. Branchini, E. Chouzenoux, V. Elvira, "Adaptive importance sampling for heavy-tailed distributions via alpha-divergence minimization", International Conference on Artificial Intelligence and Statistics (AISTATS), Valencia, Spain, 2024.
  7. O. Kviman, N. Branchini, V. Elvira, J. Lagergren, "Variational Resampling", International Conference on Artificial Intelligence and Statistics (AISTATS), Valencia, Spain, 2024.
  8. B. Cox, S. Perez-Vieites, N. Zilberstein, M. Sevilla, S. Segarra, V. Elvira, "End-to-End Learning of Gaussian Mixture Proposals Using Differentiable Particle Filters and Neural Networks", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024), Seoul, Korea, April, 2024.
  9. E. Chouzenoux and V. Elvira, "Graphical Inference in Non-Markovian Linear-Gaussian State-space Models", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024), Seoul, Korea, April, 2024.
  10. M. Lunglmayr and V. Elvira, "Redistribution Networks for Resampling", IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2023), Costa Rica, December, 2023.
  11. B. Cox, S. Perez-Vieites, N. Zilberstein, M. Sevilla, S. Segarra, V. Elvira, "State and Dynamics Estimation with the Kalman-Langevin filter", IEEE Conference on Signals, Systems, and Computers (Asilomar 2023), November 2023.
  12. O. Kviman, R. Molen, A. Hotti, S. Kurt, V. Elvira, J. Lagergren, "Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational Autoencoders", 40th International Conference on Machine Learning (ICML 2023), Hawaii, USA, July, 2023.
  13. W. Li, X. Chen, W. Wang, V. Elvira and Y. Li, "Differentiable Bootstrap Particle Filters for Regime-Switching Models", IEEE Workshop on Statistical Signal Processing (SSP 2023), Hanoi, Vietnam, July, 2023.
  14. V. Elvira, E. Chouzenoux, J. Cerda, G. Camps-Valls, "Graphs in State-Space Models for Granger Causality in Climate Science", When Causal Inference meets Statistical Analysis, Paris, France, June, 2023.
  15. K. Tsampourakis and V. Elvira, "An Augmented Gaussian Sum Filter Through a Mixture Decomposition", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023), Rhodes, Greece, June, 2023.
  16. S. Perez-Vieites and V. Elvira, "Adaptive Gaussian nested filter for parameter estimation and state tracking in dynamical systems", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023), Rhodes, Greece, June, 2023.
  17. E. Chouzenoux and V. Elvira, "GraphIT: Iterative reweighted l1 algorithm for sparse graph inference in state-space models", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023), Rhodes, Greece, June, 2023.
  18. T. Guilmeau, E. Chouzenoux, and V. Elvira, "Adaptive Simulated Annealing through Alternating Rényi Divergence Minimization", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023), Rhodes, Greece, June, 2023.
  19. B. Cox, V. Elvira, "Parameter Estimation In Sparse Linear-Gaussian State-space Models Via Reversible Jump Markov Chain Monte Carlo", 30th European Signal Processing Conference (EUSIPCO 2022), Belgrade, Serbia, September, 2022.
  20. O. Kviman, H. Melin, H. Koptagel, V. Elvira, J. Lagergren, "Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations", International Conference on Artificial Intelligence and Statistics (AISTATS), online, 2022.
  21. K. Tsampourakis and V. Elvira, "Approximating The Likelihood Ratio In Linear-gaussian State-space Models For Change Detection", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2022), Singapore, May, 2022.
  22. T. Guilmeau, É. Chouzenoux, and V. Elvira, "Proximal-based Adaptive Simulated Annealing For Global Optimization", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2022), Singapore, May, 2022.
  23. O. Straka, J. Dunik, and V. Elvira, "Importance Gauss-Hermite Gaussian Filter for Models with Non-Additive Non-Gaussian Noises", 24th International Conference on Information Fusion, Sun City, South Africa, 2021.
  24. J. Matousek, J. Dunik, M. Brandner, and V. Elvira, "Comparison of Discrete and Continuous State Estimation with Focus on Active Flux Scheme", 24th International Conference on Information Fusion, Sun City, South Africa, 2021.
  25. S. Dahiya, S. Sharma, D. Sahnan, Dhruv, V. Goel, E. Chouzenoux, V. Elvira, A. Majumdar, A. Bandhakavi, and T. Chakraborty, "Would your tweet invoke hate on the fly? forecasting hate intensity of reply threads on twitter", Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021.
  26. N. Branchini and V. Elvira "Optimized Auxiliary Particle Filters", Conference on Uncertainty in Artificial Intelligence (UAI), online, 2021.
  27. F. Llorente, L. Martino, V. Elvira, and D. Delgado, "A Nearest Neighbors Quadrature for Posterior Approximation via Adaptive Sequential Design", IEEE Workshop on Statistical Signal Processing (SSP 2021), online, 2021.
  28. T. Guilmeau, E. Chouzenoux, and V. Elvira "Simulated annealing: a review and a new scheme", IEEE Workshop on Statistical Signal Processing (SSP 2021), online, 2021.
  29. É. Chouzenoux and V. Elvira, "GraphEM: EM algorithm for blind Kalman filtering under graphical sparsity constraints", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), Barcelona, Spain, April, 2020.
  30. L. Martino, V. Elvira, and G. Camps-Valls,"Particle Group Metropolis Methods for Tracking the Leaf Area Index", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), Barcelona, Spain, April, 2020.
  31. V. Elvira and I. Santamaría, "Efficient SER Estimation for MIMO Detectors via Importance Sampling Schemes," IEEE Conference on Signals, Systems, and Computers (Asilomar 2019), November 2019.
  32. A. S. Bedi, A. Koppel, B. Sadler, and V. Elvira, "Compressed streaming importance sampling for efficient representations of localization distributions," IEEE Conference on Signals, Systems, and Computers (Asilomar 2019), November 2019.
  33. Y. Huang, É. Chouzenoux, and V. Elvira, "Particle Filtering for Online Space-Varying Blur Identification", IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2019), Guadaloupe, France, December, 2019.
  34. Y. El-Laham, V. Elvira, and M. Bugallo "Recursive Shrinkage Covariance Learning in Adaptive Importance Sampling", IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2019), Guadaloupe, France, December, 2019.
  35. V. Elvira, P. Closas, L. Martino "Gauss-Hermite Quadrature for non-Gaussian Inference via an Importance Sampling Interpretation", 27th European Signal Processing Conference (EUSIPCO 2019), A Coruña, Spain, September, 2019.
  36. Y. El-Laham, L. Martino, V. Elvira, M. F. Bugallo, "Efficient Adaptive Multiple Importance Sampling", 27th European Signal Processing Conference (EUSIPCO 2019), A Coruña, Spain, September, 2019.
  37. V. Elvira, É. Chouzenoux, "Langevin-based Strategy for Efficient Proposal Adaptation in Population Monte Carlo", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2019), Brighton, UK, May, 2019.
  38. V. Elvira, L. Martino, M. F. Bugallo, and P. M. Djuric, "In Search for Improved Auxiliary Particle Filters", 26th European Signal Processing Conference (EUSIPCO 2018), Rome, Italy, September, 2018.
  39. L. Martino, V. Elvira, G. Camps-Valls, "Distributed Particle Metropolis-Hastings schemes" , IEEE Workshop on Statistical Signal Processing (SSP 2018), Freiburg, Germany, 2018. [pdf] 
  40. L. Martino, V. Elvira, J. M\'iguez, A. Artes-Rodriguez, P. Djuric, "A comparison of clipping strategies for importance sampling", IEEE Workshop on Statistical Signal Processing (SSP 2018), Freiburg, Germany, 2018. [pdf] 
  41. Ö. Deniz Akyildiz, V. Elvira, J.Miguez, "The Incremental Proximal Method: A Probabilistic Perspective", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2018), Calgary, Canada, April, 2018. [arXiv]
  42. S. Van Vaerenbergh, I. Santamaría, V. Elvira, M. Salvattori, "Pattern Localization in Time Series through Signal-To-Model Alignment in Latent Space", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2018), Calgary, Canada, April, 2018. [arXiv] [pdf] 
  43. V. Elvira, D. Luengo, L. Martino, M. F. Bugallo, "Population Monte Carlo Schemes with Reduced Path Degeneracy", IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2017), Curaçao, Dutch Antilles, December, 2017.
  44. O. Lang, V. Elvira, and M. Huemer, ''Estimation of Real Valued Impulse Responses based on Noisy Magnitude and Phase Measurements'', IEEE Conference on Signals, Systems, and Computers (Asilomar), 2017.
  45. V. Elvira, L. Martino, D. Luengo, and M. F. Bugallo, "Novel weighting and resampling schemes in Population Monte Carlo", French National Conference on Signal and Image Processing (GRETSI 2017), Juan-les-Pines, France, September, 2017.
  46. L. Martino, V. Elvira, and D. Luengo, "Anti-tempered Layered Adaptive Importance Sampling", 22nd International Conference on Digital Signal Processing (DSP 2017), London, UK, August, 2017. [pdf] 
  47. V. Elvira, J. Miguez, and P. M. Djuric, "Robust inference techniques in state-space models with model mismatch", 61st World Statistics Congress (ISI 2017), Marrakech, Morocco, 2017.
  48. L. Martino, V. Elvira, and G. Camps-Valls, "Group Metropolis Sampling", 25th European Signal Processing Conference (EUSIPCO 2017), Kos, Greece, August, 2017. [pdf] 
  49. L. Martino, V. Elvira, and G. Camps-Valls, "Recycling Gibbs Sampling", 25th European Signal Processing Conference (EUSIPCO 2017), Kos, Greece, August, 2017. [pdf] 
  50. M. F. Bugallo, V. Elvira, and L. Martino, "A new strategy for effective learning in population monte carlo sampling," IEEE Conference on Signals, Systems, and Computers (Asilomar 2016), pp. 1540-1544, Pacific Groove, California, USA, November 2016. [pdf] 
  51. S. Van Vaerenbergh, J. Fernandez-Bes, and V. Elvira, “On The Relationship Between Online Gaussian Process Regression And Kernel Least Mean Squares Algorithms”, IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2016), Salerno, Italy, September, 2016.
  52. V. Elvira, J. Miguez, and P. M. Djuric, "A Novel Algorithm for Adapting the Number of Particles in Particle Filtering", IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2016), Rio de Janeiro, Brazil, July, 2016.
  53. L. Martino, V. Elvira, D. Luengo, and F. Louzada, " Adaptive Population Importance Samplers: A General Perspective", IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2016), Rio de Janeiro, Brazil, July, 2016.
  54. V. Elvira, L. Martino, D. Luengo, and M. F. Bugallo, "Novel weighting schemes with non-disjoint mixtures of proposals in multiple importance sampling", IEEE Workshop on Statistical Signal Processing (SSP 2016), Mallorca, Spain, June, 2016.
  55. L. Martino, V. Elvira, and F. Lozada, "Alternative Effective Sample Size measures for Importance Sampling", IEEE Workshop on Statistical Signal Processing (SSP 2016), Mallorca, Spain, June, 2016. [pdf] 
  56. L. Martino, V. Elvira, and F. Louzada, "Weighting a resampled particle in Sequential Monte Carlo", IEEE Workshop on Statistical Signal Processing (SSP 2016), Mallorca, Spain, June, 2016.
  57. V. Elvira, J. Miguez, and P. M. Djuric, "Online Adaptation of the Number of Particles of Sequential Monte Carlo Methods", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2016), Shanghai, China, March, 2016.
  58. L. Martino, V. Elvira, D. Luengo, F. Louzada, "Parallel Metropolis chains with cooperative adaptation", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2016), Shanghai, China, March, 2016. [arXiv]
  59. D. Luengo, G. Ríos-Muñoz, V. Elvira, A. Artés-Rodríguez, "A hierarchical algorithm for causality discovery among atrial fibrillation electrograms", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2016), Shanghai, China, March, 2016. [pdf] 
  60. D. Luengo, V. Elvira, "Latent variable analysis of causal interactions in atrial fibrillation electrograms", 42th Computing in Cardiology, Vancouver, Canada, September, 2016. [pdf] 
  61. V. Elvira, L. Martino, D. Luengo, and M. F. Bugallo, "On Sample Generation and Weight Calculation in Multiple Importance Sampling", IEEE Conference on Signals, Systems, and Computers (ASILOMAR 2015), Pacific Groove, California, USA, November 2015. [pdf] 
  62. D. Luengo, L. Martino, V. Elvira, M. F. Bugallo, "Bias Correction for Distributed Bayesian Estimators", IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2015), Cancún, México, December, 2015.
  63. D. Luengo, G. Ríos-Muñoz, V. Elvira, "Causality Analysis of Atrial Fibrillation Electrograms", 42th Computing in Cardiology, Nice, France, September, 2015. [pdf] 
  64. L. Martino, V. Elvira, D. Luengo, J. Corander, "Interacting Parallel Markov Adaptive Importance Sampling", 23th European Signal Processing Conference (EUSIPCO 2015), Nice, France, August, 2015.
  65. V. Elvira, L. Martino, D. Luengo, J. Corander, "A Gradient Adaptive Population Importance Sampler", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2015), Brisbane, Australia, April, 2015. [pdf] 
  66. J. Fernández-Bes, V. Elvira, S. Van Vaerenbergh, "A Probabilistic Least-Mean-Squares Filter", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2015), Brisbane, Australia, April, 2015. [arXiv] [pdf] 
  67. L. Martino, V. Elvira, D. Luengo, A. Artés-Rodríguez, J. Corander, "Smelly Parallel MCMC Chains", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2015), Brisbane, Australia, April, 2015. [pdf] 
  68. D. Luengo, L. Martino, V. Elvira, M. F. Bugallo, "Efficient Linear Combination of Partial Monte Carlo Estimators", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2015), Brisbane, Australia, April, 2015. [pdf] 
  69. L. Martino, V. Elvira, D. Luengo, A. Artés-Rodríguez, J. Corander, "Orthogonal MCMC Algorithms", IEEE Statistical Signal Processing Workshop (SSP 2014), Gold Coast, Australia, June, 2014. [pdf] 
  70. V. Elvira, A. Nazábal, A. Artés-Rodríguez, "A Novel Feature Extraction Technique for Human Activity Recognition", IEEE Statistical Signal Processing Workshop (SSP 2014), Gold Coast, Australia, June, 2014. [pdf] 
  71. L. Martino, V. Elvira, D. Luengo, J. Corander, "An Adaptive Population Importance Sampler", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2014), Florence, Italy, May, 2014. [pdf] 
  72. L. Martino, V. Elvira, D. Luengo, J. Corander, "MCMC-Driven Adaptive Multiple Importance Sampling", 12th Brazilian Meeting on Bayesian Statistics, Atibaia, Brazil, March, 2014.
  73. R. Eickoff, K. Tittelbach-Helmrich, M. Wickert, J. Wagner, U. Mayer, V. Elvira, J. Ibáñez, Z. Stamenkovic, and F. Ellinger, "Physical layer amendments for MIMO features in 802.11 a", Future Network & Mobile Summit (FutureNetw), Warsaw, Poland, June, 2011. [pdf] 
  74. V. Elvira, J. Ibáñez, I. Santamaría, M. Krstic, K. Tittelbach-Helmrich, and Z. Stamenkovic, "Baseband processor for RF-MIMO WLAN", 17th IEEE International Conference on Electronics, Circuits, and Systems (ICECS 2010), Athens, Greece, December, 2010. [pdf] 
  75. Z. Stamenkovic, K. Tittelbach-Helmrich, M. Krstic, J. Ibáñez, V. Elvira, and I. Santamaría, "MAC and Baseband Hardware Platforms for RF-MIMO WLAN", 5th European Conference on Circuits and Systems for Communications, Belgrade, Serbia, November, 2010. [pdf] 
  76. J. Vía, I. Santamaría, V. Elvira, and R. Eickhoff, "A general Pre-FFT criterion for MIMO-OFDM beamforming", IEEE International Conference on Communications (ICC 2010), Cape Town, South Africa, May, 2010. [pdf] 
  77. V. Elvira, and J. Vía, "Diversity Techniques for RF-Beamforming in MIMO-OFDM Systems: Design and Performance Evaluation", 17th European Signal Processing Conference (EUSIPCO 2009), Glasgow, United Kingdom, August, 2009. [pdf] 
  78. J. Vía, V. Elvira, I. Santamaría, and R. Eickhoff, "Analog Antenna Combining for Maximum Capacity under OFDM Transmissions", IEEE International Conference on Communications (ICC 2009), Dresden, Germany, June, 2009. [pdf] 
  79. J. Vía, V. Elvira, J. Ibáñez, and I. Santamaría, "Optimal Precoding for a Novel RF-MIMO Scheme in Transmit Correlated Rayleigh Channels", 10th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2009), Perugia, Italy, June, 2009. [pdf] 
  80. J. Vía, V. Elvira, I. Santamaría, and R. Eickhoff, "Minimum BER beamforming in the RF domain for OFDM transmissions and linear receivers", IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP 2009), Taipei, Taiwan, April, 2009. [pdf] 
  81. I. Santamaría, V. Elvira, J. Vía, D. Ramírez, J. Pérez, J. Ibáñez, R. Eickhoff, and F. Ellinger, "Optimal MIMO transmission schemes with adaptive antenna combining in the RF path", 16th European Signal Processing Conference (EUSIPCO 2008), Lausanne, Switzerland, August, 2008. [pdf] 

Book chapters

  • L. Martino, V. Elvira, D. Luengo, and J. Corander, "MCMC-Driven Adaptive Multiple Importance Sampling", Interdisciplinary Bayesian Statistics, A. Polpo de Campos (editor): Springer, 2015.
  • I. Santamaría, J. Vía, V. Elvira, J. Ibáñez, J. Pérez, R. Eickhoff, and U. Mayer, "Low-Cost and Compact RF-MIMO Transceivers", Handbook of Smart Antennas for RFID Systems, N. C. Karmakar (editor): John Wiley & Sons , 2010.

PhD dissertation

  • V. Elvira, Baseband processing in analog combining MIMO systems: from theoretical design to FPGA implementation, University of Cantabria, 2011. Google Scholar BibTex [pdf]