Tobías I. Liaudat

According to our database, Tobías I. Liaudat authored at least 11 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Bayesian model selection and misspecification testing in imaging inverse problems only from noisy and partial measurements.

Tom Sprunck, Marcelo Pereyra, Tobías I. Liaudat

CoRR, October, 2025

Generative imaging for radio interferometry with fast uncertainty quantification.

Matthijs Mars, Tobías I. Liaudat, Jessica J. Whitney, Marta M. Betcke, Jason D. McEwen

CoRR, July, 2025

LoFi: Neural Local Fields for Scalable Image Reconstruction.

AmirEhsan Khorashadizadeh, Tobías I. Liaudat, Tianlin Liu, Jason D. McEwen, Ivan Dokmanic

IEEE Trans. Computational Imaging, 2025

2024

LoFi: Scalable Local Image Reconstruction with Implicit Neural Representation.

AmirEhsan Khorashadizadeh, Tobías I. Liaudat, Tianlin Liu, Jason D. McEwen, Ivan Dokmanic

CoRR, 2024

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

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

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

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

PhD thesis, 2022

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

2021

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

2020

Faster and better sparse blind source separation through mini-batch optimization.

Christophe Kervazo, Tobías I. Liaudat, Jérôme Bobin

Digit. Signal Process., 2020