1k citations · 1k across the 3 of their papers we have counts for
4 papers
LAION-5B: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu +13
Groundbreaking language-vision architectures like CLIP and DALL-E proved the utility of training on large amounts of noisy image-text data, without relying on expensive accurate la…
JUWELS Booster -- A Supercomputer for Large-Scale AI Research
Stefan Kesselheim, Andreas Herten, Kai Krajsek +15
In this article, we present JUWELS Booster, a recently commissioned high-performance computing system at the Jülich Supercomputing Center. With its system architecture, most import…
Spurious samples in deep generative models: bug or feature?
Balázs Kégl, Mehdi Cherti, Akın Kazakçı
Traditional wisdom in generative modeling literature is that spurious samples that a model can generate are errors and they should be avoided. Recent research, however, has shown i…
Machine learning for classification and quantification of monoclonal antibody preparations for cancer therapy
Laetitia Le, Camille Marini, Alexandre Gramfort +9
Monoclonal antibodies constitute one of the most important strategies to treat patients suffering from cancers such as hematological malignancies and solid tumors. In order to guar…