no code implementations • 17 Jul 2023 • Samuele Papa, David M. Knigge, Riccardo Valperga, Nikita Moriakov, Miltos Kofinas, Jan-Jakob Sonke, Efstratios Gavves
Conventional Computed Tomography (CT) methods require large numbers of noise-free projections for accurate density reconstructions, limiting their applicability to the more complex class of Cone Beam Geometry CT (CBCT) reconstruction.
1 code implementation • 15 Jun 2023 • Gabriel Bénédict, Olivier Jeunen, Samuele Papa, Samarth Bhargav, Daan Odijk, Maarten de Rijke
In this paper we propose RecFusion, which comprise a set of diffusion models for recommendation.
no code implementations • 18 Apr 2022 • Samuele Papa, Ole Winther, Andrea Dittadi
Understanding which inductive biases could be helpful for the unsupervised learning of object-centric representations of natural scenes is challenging.
1 code implementation • 1 Jul 2021 • Andrea Dittadi, Samuele Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello
The idea behind object-centric representation learning is that natural scenes can better be modeled as compositions of objects and their relations as opposed to distributed representations.