Robust Covariance Adaptation in Adaptive Importance Sampling. - Yousef El-Laham; Victor Elvira; Mónica F. Bugallo (IEEE Signal Process. Lett., 2018)

Recursive Shrinkage Covariance Learning in Adaptive Importance Sampling. - Yousef El-Laham; Víctor Elvira; Mónica F. Bugallo (CAMSAP, 2019)

A Novel Particle Filter for High-Dimensional Systems Using Penalized Perturbations. - Yousef El-Laham; Zahraa Krayem; Jessica Maghakian; Mónica F. Bugallo (EUSIPCO, 2019)

Efficient Adaptive Multiple Importance Sampling. - Yousef El-Laham; Luca Martino; Víctor Elvira; Mónica F. Bugallo (EUSIPCO, 2019)

A Variational Adaptive Population Importance Sampler. - Yousef El-Laham; Petar M. Djuric; Mónica F. Bugallo (ICASSP, 2019)

Particle Filtering Under General Regime Switching. - Yousef El-Laham; Liu Yang; Petar M. Djuric; Mónica F. Bugallo (EUSIPCO, 2020)

Enhanced Mixture Population Monte Carlo Via Stochastic Optimization and Markov Chain Monte Carlo Sampling. - Yousef El-Laham; Petar M. Djuric; Mónica F. Bugallo (ICASSP, 2020)

A Particle Gibbs Sampling Approach to Topology Inference in Gene Regulatory Networks. - Marija Iloska; Yousef El-Laham; Mónica F. Bugallo (ICASSP, 2020)

Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters. - Liu Yang; Hechuan Wang; Yousef El-Laham; José Ignacio Lamas Fonte; David Trillo Pérez; Mónica F. Bugallo (ICASSP, 2020)

Stochastic Gradient Population Monte Carlo. - Yousef El-Laham; Mónica F. Bugallo (IEEE Signal Process. Lett., 2020)

Particle Gibbs Sampling for Regime-Switching State-Space Models. - Yousef El-Laham; Liu Yang; Heather J. Lynch; Petar M. Djuric; Mónica F. Bugallo (ICASSP, 2021)

Robust Frequency and Phase Estimation for Three-Phase Power Systems Using a Bank of Kalman Filters. - Zahraa Krayem; Yousef El-Laham; Mónica F. Bugallo (IEEE Signal Process. Lett., 2021)

Policy Gradient Importance Sampling for Bayesian Inference. - Yousef El-Laham; Mónica F. Bugallo (IEEE Trans. Signal Process., 2021)

StyleTime: Style Transfer for Synthetic Time Series Generation. - Yousef El-Laham; Svitlana Vyetrenko (ICAIF, 2022)

HyperTime: Implicit Neural Representation for Time Series. - Elizabeth Fons; Alejandro Sztrajman; Yousef El-Laham; Alexandros Iosifidis; Svitlana Vyetrenko (CoRR, 2022)

DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift. - Defu Cao; Yousef El-Laham; Loc Trinh; Svitlana Vyetrenko; Yan Liu 002 (CoRR, 2022)

Fusion of Probability Density Functions. - Günther Koliander; Yousef El-Laham; Petar M. Djuric; Franz Hlawatsch (Proc. IEEE, 2022)

Graphical network and topology estimation for autoregressive models using Gibbs sampling. - Marija Iloska; Yousef El-Laham; Mónica F. Bugallo (Signal Process., 2022)

Deep Gaussian mixture ensembles. - Yousef El-Laham; Niccolò Dalmasso; Elizabeth Fons; Svitlana Vyetrenko (UAI, 2023)

MADS: Modulated Auto-Decoding SIREN for time series imputation. - Tom Bamford; Elizabeth Fons; Yousef El-Laham; Svitlana Vyetrenko (CoRR, 2023)

Augment on Manifold: Mixup Regularization with UMAP. - Yousef El-Laham; Elizabeth Fons; Dillon Daudert; Svitlana Vyetrenko (ICASSP, 2024)

Neural Stochastic Differential Equations with Change Points: A Generative Adversarial Approach. - Zhongchang Sun; Yousef El-Laham; Svitlana Vyetrenko (ICASSP, 2024)

Synthetic Data Applications in Finance. - Vamsi K. Potluru; Daniel Borrajo; Andrea Coletta; Niccolò Dalmasso; Yousef El-Laham; Elizabeth Fons; Mohsen Ghassemi; Sriram Gopalakrishnan; Vikesh Gosai; Eleonora Kreacic; Ganapathy Mani; Saheed Obitayo; et al. (CoRR, 2024)

A Language Model-Guided Framework for Mining Time Series with Distributional Shifts. - Haibei Zhu; Yousef El-Laham; Elizabeth Fons; Svitlana Vyetrenko (CoRR, 2024)

iHyperTime: Interpretable Time Series Generation with Implicit Neural Representations. - Elizabeth Fons; Alejandro Sztrajman; Yousef El-Laham; Andrea Coletta; Alexandros Iosifidis; Svitlana Vyetrenko (Trans. Mach. Learn. Res., 2024)

Fusion of Information in Multiple Particle Filtering in the Presence of Unknown Static Parameters. - Xiaokun Zhao; Marija Iloska; Yousef El-Laham; Mónica F. Bugallo (ICASSP, 2025)

Mixup Regularization: A Probabilistic Perspective. - Yousef El-Laham; Niccolò Dalmasso; Svitlana Vyetrenko; Vamsi K. Potluru; Manuela Veloso (UAI, 2025)

Variational Neural Stochastic Differential Equations with Change Points. - Yousef El-Laham; Zhongchang Sun; Haibei Zhu; Tucker Balch; Svitlana Vyetrenko (Trans. Mach. Learn. Res., 2025)

LSCD: Lomb-Scargle Conditioned Diffusion for Time series Imputation. - Elizabeth Fons; Alejandro Sztrajman; Yousef El-Laham; Luciana Ferrer; Svitlana Vyetrenko; Manuela Veloso (CoRR, 2025)