Generative Fractional Diffusion Models

no code implementations • 26 Oct 2023 • Gabriel Nobis, Marco Aversa, Maximilian Springenberg, Michael Detzel, Stefano Ermon, Shinichi Nakajima, Roderick Murray-Smith, Sebastian Lapuschkin, Christoph Knochenhauer, Luis Oala, Wojciech Samek

We generalize the continuous time framework for score-based generative models from an underlying Brownian motion (BM) to an approximation of fractional Brownian motion (FBM).

Data Models for Dataset Drift Controls in Machine Learning With Optical Images

1 code implementation • 4 Nov 2022 • Luis Oala, Marco Aversa, Gabriel Nobis, Kurt Willis, Yoan Neuenschwander, Michèle Buck, Christian Matek, Jerome Extermann, Enrico Pomarico, Wojciech Samek, Roderick Murray-Smith, Christoph Clausen, Bruno Sanguinetti

This limits our ability to study and understand the relationship between data generation and downstream machine learning model performance in a physically accurate manner.

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