3 citations · 3 across the 4 of their papers we have counts for
4 papers
Contrastive Joint-Embedding Prediction for Representation Learning in Structural MRI
Fabian Mager, Lars Kai Hansen
Self-supervised learning offers a compelling approach for medical imaging, where labeled data are scarce and acquisition costs are high. We present COJEPA, a self-supervised framew…
On the modality gap and the contrastive loss in multi-modal representation learning
Fabian Mager, Hiba Nassar, Lars Kai Hansen
We study the modality gap in CLIP-style dual-encoder contrastive learning, where image and text embeddings remain misaligned despite being trained in a shared space. We argue that…
Improving Relative Representations with Learned Anchors and Whitened Inner Products
Oscar Thorsted Svendsen, Nikolaj Holst Jakobsen, Fabian Mager +1
Independently trained neural models typically converge to incompatible latent representations, creating a fundamental barrier to highly modular AI systems. While Relative Represent…
On convex decision regions in deep network representations
Lenka Tětková, Thea Brüsch, Teresa Karen Scheidt +5
Current work on human-machine alignment aims at understanding machine-learned latent spaces and their correspondence to human representations. G{ä}rdenfors' conceptual spaces is a…