Publications

(2024). Efficient Frequency Selective Surface Analysis via End-to-End Model-Based Learning.

Cite arXiv URL

(2024). Unsupervised Learning for Gain-Phase Impairment Calibration in ISAC Systems.

Cite arXiv URL

(2024). Optimal Blind Focusing on Perturbation-Inducing Targets in Sub-Unitary Complex Media. Laser & Photonics Reviews.

Cite DOI URL

(2024). Model-based learning for multi-antenna multi-frequency location-to-channel mapping.

Cite arXiv URL

(2024). Optimizing Multicarrier Multiantenna Systems for LoS Channel Charting. IEEE Transactions on Wireless Communications.

Cite DOI arXiv ieeeXplore

(2024). Experimentally realized physical-model-based frugal wave control in metasurface-programmable complex media. Nature Communications.

Cite ArXiv Publisher

(2024). On the Tacit Linearity Assumption in Common Cascaded Models of RIS-Parametrized Wireless Channels. IEEE Transactions on Wireless Communications.

Cite DOI

(2023). Model-based Deep Learning for Beam Prediction based on a Channel Chart.

Cite arXiv

(2023). Semi-Supervised End-to-End Learning for Integrated Sensing and Communications.

Cite arXiv

(2023). Optimizing Multicarrier Multiantenna Systems for LoS Channel Charting.

Cite arXiv

(2023). Model-based Deep Learning for High-Dimensional Periodic Structures.

Cite arXiv

(2023). Model-based learning for location-to-channel mapping.

Cite arXiv

(2023). Experimentally realized physical-model-based wave control in metasurface-programmable complex media.

Cite arXiv

(2023). Model-Driven End-to-End Learning for Integrated Sensing and Communication. ICC 2023 - IEEE International Conference on Communications.

Cite DOI

(2023). Efficient Deep Unfolding for SISO-OFDM Channel Estimation. ICC 2023 - IEEE International Conference on Communications.

Cite DOI

(2023). On the Tacit Linearity Assumption in Common Cascaded Models of RIS-Parametrized Wireless Channels.

Cite arXiv

(2023). Model-Based End-to-End Learning for Multi-Target Integrated Sensing and Communication.

Cite arXiv

(2022). Channel charting based beamforming. 2022 56th Asilomar Conference on Signals, Systems, and Computers.

Cite DOI arXiv

(2022). mpNet: Variable Depth Unfolded Neural Network for Massive MIMO Channel Estimation. IEEE Transactions on Wireless Communications.

Cite DOI arXiv

(2022). Leveraging triplet loss and nonlinear dimensionality reduction for on-the-fly channel charting. 2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC).

Cite DOI arXiv

(2022). Deep Learning for Location Based Beamforming with Nlos Channels. 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Cite DOI arXiv

(2022). Model-Driven End-to-End Learning for Integrated Sensing and Communication.

Cite arXiv

(2022). Efficient Deep Unfolding for SISO-OFDM Channel Estimation.

Cite arXiv

(2021). Efficient Channel Charting via Phase-Insensitive Distance Computation. IEEE Wireless Communications Letters.

Cite DOI arXiv

(2021). Similarity-Based Prediction for Channel Mapping and User Positioning. IEEE Communications Letters.

Cite DOI arXiv

(2020). On the Computation of Integrals of Bivariate Gaussian Distribution. 2020 IEEE Symposium on Computers and Communications (ISCC).

Cite DOI hal

(2020). Channel Estimation: Unified View of Optimal Performance and Pilot Sequences. IEEE Transactions on Signal Processing.

Cite DOI arXiv

(2019). Exploiting the Massive MIMO Channel Structural Properties for Minimization of Channel Estimation Error and Training Overhead. IEEE Access.

Cite DOI hal

(2019). Massive MIMO Channel Estimation taking into account spherical waves. 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

Cite DOI hal

(2018). MIMO Channel Hardening for Ray-based Models. 2018 14th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob).

Cite DOI hal

(2018). Parametric Channel Estimation for Massive MIMO. 2018 IEEE Statistical Signal Processing Workshop (SSP).

Cite DOI arXiv

(2018). Approximate Fast Graph Fourier Transforms via Multilayer Sparse Approximations. IEEE Transactions on Signal and Information Processing over Networks.

Cite DOI arXiv

(2017). Analyzing the approximation error of the fast graph Fourier transform. 2017 51st Asilomar Conference on Signals, Systems, and Computers.

Cite DOI arXiv

(2016). Flexible Multilayer Sparse Approximations of Matrices and Applications. IEEE Journal of Selected Topics in Signal Processing.

Cite DOI arXiv

(2016). Are there approximate fast fourier transforms on graphs?. 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Cite DOI hal

(2015). FAμST: Speeding up linear transforms for tractable inverse problems. 2015 23rd European Signal Processing Conference (EUSIPCO).

Cite DOI Researchgate

(2015). Chasing butterflies: In search of efficient dictionaries. 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Cite DOI hal

(2015). Text-informed audio source separation. example-based approach using non-negative matrix partial co-factorization. Journal of Signal Processing Systems.

Cite

(2013). Text-informed audio source separation using nonnegative matrix partial co-factorization. 2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

Cite DOI

(2013). Maximum likelihood estimation of clutter subspace in non homogeneous noise context. 2013 21st European Signal Processing Conference (EUSIPCO).

Cite hal