26 citations · 28 across the 4 of their papers we have counts for
4 papers
Noise-Robust Conditional Flow Matching: Generating Clean Samples from Noisy Datasets
Adrian Urbański, Gabriel della Maggiora, Artur Yakimovich
Generative models learn the statistical properties of their training data, so high-quality generation depends on clean and representative datasets. In scientific imaging, acquisiti…
Single Exposure Quantitative Phase Imaging with a Conventional Microscope using Diffusion Models
Gabriel della Maggiora, Luis Alberto Croquevielle, Harry Horsley +2
Phase imaging is gaining importance due to its applications in fields like biomedical imaging and material characterization. In biomedical applications, it can provide quantitative…
Conditional Variational Diffusion Models
Gabriel della Maggiora, Luis Alberto Croquevielle, Nikita Deshpande +3
Inverse problems aim to determine parameters from observations, a crucial task in engineering and science. Lately, generative models, especially diffusion models, have gained popul…
Microscopy image reconstruction with physics-informed denoising diffusion probabilistic model
Rui Li, Gabriel della Maggiora, Vardan Andriasyan +4
Light microscopy is a widespread and inexpensive imaging technique facilitating biomedical discovery and diagnostics. However, light diffraction barrier and imperfections in optics…