21 citations · 38 across the 5 of their papers we have counts for
5 papers
CoralBay: A Self-Supervised CT Foundation Model
Ioannis Gatopoulos, Nicolas Känzig, Sebastian Otálora +1
Self-supervised learning has enabled large-scale pre-training on 2D natural images, producing general-purpose visual representations that transfer effectively across tasks. However…
Towards Large-Scale Training of Pathology Foundation Models
kaiko. ai, Nanne Aben, Edwin D. de Jong +7
Driven by the recent advances in deep learning methods and, in particular, by the development of modern self-supervised learning algorithms, increased interest and efforts have bee…
Self-supervised Video Representation Learning with Cross-Stream Prototypical Contrasting
Martine Toering, Ioannis Gatopoulos, Maarten Stol +1
Instance-level contrastive learning techniques, which rely on data augmentation and a contrastive loss function, have found great success in the domain of visual representation lea…
Self-Supervised Variational Auto-Encoders
Ioannis Gatopoulos, Jakub M. Tomczak
Density estimation, compression and data generation are crucial tasks in artificial intelligence. Variational Auto-Encoders (VAEs) constitute a single framework to achieve these go…
Super-resolution Variational Auto-Encoders
Ioannis Gatopoulos, Maarten Stol, Jakub M. Tomczak
The framework of variational autoencoders (VAEs) provides a principled method for jointly learning latent-variable models and corresponding inference models. However, the main draw…