Kalmannet: Data-Driven Kalman Filtering. - Guy Revach; Nir Shlezinger; Ruud J. G. van Sloun; Yonina C. Eldar (ICASSP, 2021)

On the Influence of Home Appliances on the Smartphone's Inertial Sensors. - Shunit Truzman; Guy Revach; Itzik Klein (IEEE SENSORS, 2021)

Unsupervised Learned Kalman Filtering. - Guy Revach; Nir Shlezinger; Timur Locher; Xiaoyong Ni; Ruud J. G. van Sloun; Yonina C. Eldar (EUSIPCO, 2022)

Uncertainty in Data-Driven Kalman Filtering for Partially Known State-Space Models. - Itzik Klein; Guy Revach; Nir Shlezinger; Jonas E. Mehr; Ruud J. G. van Sloun; Yonina C. Eldar (ICASSP, 2022)

Deep Augmented Music Algorithm for Data-Driven Doa Estimation. - Julian P. Merkofer; Guy Revach; Nir Shlezinger; Ruud J. G. van Sloun (ICASSP, 2022)

RTSNet: Deep Learning Aided Kalman Smoothing. - Xiaoyong Ni; Guy Revach; Nir Shlezinger; Ruud J. G. van Sloun; Yonina C. Eldar (ICASSP, 2022)

Composite Anomaly Detection via Hierarchical Dynamic Search. - Benjamin Wolff; Tomer Gafni; Guy Revach; Nir Shlezinger; Kobi Cohen (ISIT, 2022)

KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics. - Guy Revach; Nir Shlezinger; Xiaoyong Ni; Adrià López Escoriza; Ruud J. G. van Sloun; Yonina C. Eldar (IEEE Trans. Signal Process., 2022)

Learned Kalman Filtering in Latent Space with High-Dimensional Data. - Itay Buchnik; Damiano Steger; Guy Revach; Ruud J. G. van Sloun; Tirza Routtenberg; Nir Shlezinger (ICASSP, 2023)

LQGNET: Hybrid Model-Based and Data-Driven Linear Quadratic Stochastic Control. - Solomon Goldgraber Casspi; Oliver Hüsser; Guy Revach; Nir Shlezinger (ICASSP, 2023)

Kalmanbot: Kalmannet-Aided Bollinger Bands for Pairs Trading. - Haoran Deng; Guy Revach; Hai Morgenstern; Nir Shlezinger (ICASSP, 2023)

Hierarchical Filtering With Online Learned Priors for ECG Denoising. - Timur Locher; Guy Revach; Nir Shlezinger; Ruud J. G. van Sloun; Rik Vullings (ICASSP, 2023)

Deep Root Music Algorithm for Data-Driven Doa Estimation. - Dor Haim Shmuel; Julian P. Merkofer; Guy Revach; Ruud J. G. van Sloun; Nir Shlezinger (ICASSP, 2023)

Outlier-Insensitive Kalman Filtering Using NUV Priors. - Shunit Truzman; Guy Revach; Nir Shlezinger; Itzik Klein (ICASSP, 2023)

Outlier-Insensitive Kalman Filtering: Theory and Applications. - Shunit Truzman; Guy Revach; Nir Shlezinger; Itzik Klein (CoRR, 2023)

Anomaly Search Over Discrete Composite Hypotheses in Hierarchical Statistical Models. - Tomer Gafni; Benjamin Wolff; Guy Revach; Nir Shlezinger; Kobi Cohen (IEEE Trans. Signal Process., 2023)

RTSNet: Learning to Smooth in Partially Known State-Space Models. - Guy Revach; Xiaoyong Ni; Nir Shlezinger; Ruud J. G. van Sloun; Yonina C. Eldar (IEEE Trans. Signal Process., 2023)

Uncertainty Quantification in Deep Learning Based Kalman Filters. - Yehonatan Dahan; Guy Revach; Jindrich Duník; Nir Shlezinger (ICASSP, 2024)

Adaptive Kalmannet: Data-Driven Kalman Filter with Fast Adaptation. - Xiaoyong Ni; Guy Revach; Nir Shlezinger (ICASSP, 2024)

Exploring the trade-off between deep-learning and explainable models for brain-machine interfaces. - Luis Cubillos; Guy Revach; Matthew Mender; Joseph T. Costello; Hisham Temmar; Aren Hite; Diksha Anoop Kumar Zutshi; Dylan Wallace; Xiaoyong Ni; Madison Kelberman; Matt S. Willsey; Ruud van Sloun; et al. (NeurIPS, 2024)

AI-Aided Kalman Filters. - Nir Shlezinger; Guy Revach; Anubhab Ghosh; Saikat Chatterjee; Shuo Tang; Tales Imbiriba; Jindrich Duník; Ondrej Straka; Pau Closas; Yonina C. Eldar (CoRR, 2024)

Latent-KalmanNet: Learned Kalman Filtering for Tracking From High-Dimensional Signals. - Itay Buchnik; Guy Revach; Damiano Steger; Ruud J. G. van Sloun; Tirza Routtenberg; Nir Shlezinger (IEEE Trans. Signal Process., 2024)

Neural Augmented Kalman Filtering With Bollinger Bands for Pairs Trading. - Amit Milstein; Guy Revach; Haoran Deng; Hai Morgenstern; Nir Shlezinger (IEEE Trans. Signal Process., 2024)

HKF: Hierarchical Kalman Filtering With Online Learned Evolution Priors for Adaptive ECG Denoising. - Guy Revach; Timur Locher; Nir Shlezinger; Ruud J. G. van Sloun; Rik Vullings (IEEE Trans. Signal Process., 2024)

DA-MUSIC: Data-Driven DoA Estimation via Deep Augmented MUSIC Algorithm. - Julian P. Merkofer; Guy Revach; Nir Shlezinger; Tirza Routtenberg; Ruud J. G. van Sloun (IEEE Trans. Veh. Technol., 2024)

Bayesian KalmanNet: Quantifying Uncertainty in Deep Learning Augmented Kalman Filter. - Yehonatan Dahan; Guy Revach; Jindrich Duník; Nir Shlezinger (IEEE Trans. Signal Process., 2025)

SubspaceNet: Deep Learning-Aided Subspace Methods for DoA Estimation. - Dor Haim Shmuel; Julian P. Merkofer; Guy Revach; Ruud J. G. van Sloun; Nir Shlezinger (IEEE Trans. Veh. Technol., 2025)