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stat.ML2026
Iterating Consistency Models: Stability, Error Bounds and Noise Schedules
Alessio Spagnoletti, Abdul-Lateef Haji-Ali, Andrés Almansa +3
Consistency models (CMs) have become a leading approach for generating high-quality samples in few steps. However, adding steps can improve or degrade sample quality in ways that a…
cs.CV2026
BAM! Bayesian Anything Model: a foundation model for generative computational imaging
Alessio Spagnoletti, Charlesquin Kemajou Mbakam, Jonathan Spence +2
Generative models are transforming Bayesian computational imaging, yet the field still lacks physics-aware foundation models. Current practice falls into two camps. Large foundatio…
stat.ML2026
Consistency Regularised Gradient Flows for Inverse Problems
Alessio Spagnoletti, Tim Y. J. Wang, Marcelo Pereyra +1
Vision-Language Latent Diffusion Models (LDMs) (Rombach et al., 2022) provide powerful generative priors for inverse problems. However, existing LDM-based inverse solvers typically…