papers
Publications (6)
astro-ph.CO2025
Distribution-free uncertainty quantification for inverse problems: application to weak lensing mass mapping
Hubert Leterme, Jalal Fadili, Jean-Luc Starck
cs.CV2024
From CNNs to Shift-Invariant Twin Models Based on Complex Wavelets
Hubert Leterme, Kévin Polisano, Valérie Perrier +1
astro-ph.CO2026
A plug-and-play approach with fast uncertainty quantification for weak lensing mass mapping
Hubert Leterme, Andreas Tersenov, Jalal Fadili +1
The paper presents PnPMass, a plug‑and‑play algorithm that reconstructs dark‑matter maps from weak‑lensing shear data using a single deep‑learning denoiser combined with gradient d…
#weak lensing#mass mapping#deep learning#uncertainty quantification
cs.CV2025
Disentangling Modes and Interference in the Spectrogram of Multicomponent Signals
Kévin Polisano, Sylvain Meignen, Nils Laurent +1
astro-ph.CO2024
Galaxy-Point Spread Function correlations as a probe of weak-lensing systematics with UNIONS data
Sacha Guerrini, Martin Kilbinger, Hubert Leterme +6
cs.CV2025
On the Shift Invariance of Max Pooling Feature Maps in Convolutional Neural Networks
Hubert Leterme, Kévin Polisano, Valérie Perrier +1