Faster and better sparse blind source separation through mini-batch optimization. - Christophe Kervazo; Tobías I. Liaudat; Jérôme Bobin (Digit. Signal Process., 2020)

Rethinking the modeling of the instrumental response of telescopes with a differentiable optical model. - Tobías I. Liaudat; Jean-Luc Starck; Martin Kilbinger; Pierre-Antoine Frugier (CoRR, 2021)

Rethinking data-driven point spread function modeling with a differentiable optical model. - Tobías I. Liaudat; Jean-Luc Starck; Martin Kilbinger; Pierre-Antoine Frugier (CoRR, 2022)

Data-driven modelling of ground-based and space-based telescope's point spread functions. (Modélisation guidée par les données des fonctions d'étalement du point des télescopes terrestres et spatiaux). - Tobías I. Liaudat (2022)

Point spread function modelling for astronomical telescopes: a review focused on weak gravitational lensing studies. - Tobías I. Liaudat; Jean-Luc Starck; Martin Kilbinger; Pierre-Antoine Frugier (CoRR, 2023)

Scalable Bayesian uncertainty quantification with data-driven priors for radio interferometric imaging. - Tobías I. Liaudat; Matthijs Mars; Matthew A. Price; Marcelo Pereyra; Marta M. Betcke; Jason D. McEwen (CoRR, 2023)

Uncertainty quantification for fast reconstruction methods using augmented equivariant bootstrap: Application to radio interferometry. - Mostafa Cherif; Tobías I. Liaudat; Jonathan Kern; Christophe Kervazo; Jérôme Bobin (CoRR, 2024)

LoFi: Scalable Local Image Reconstruction with Implicit Neural Representation. - AmirEhsan Khorashadizadeh; Tobías I. Liaudat; Tianlin Liu; Jason D. McEwen; Ivan Dokmanic (CoRR, 2024)

Generative imaging for radio interferometry with fast uncertainty quantification. - Matthijs Mars; Tobías I. Liaudat; Jessica J. Whitney; Marta M. Betcke; Jason D. McEwen (CoRR, 2025)