9 papers
Leveraging the Structure of Medical Data for Improved Representation Learning
Andrea Agostini, Sonia Laguna, Alain Ryser +7
Building generalizable medical AI systems requires pretraining strategies that are data-efficient and domain-aware. Unlike internet-scale corpora, clinical datasets such as MIMIC-C…
Interpretable Reward Modeling with Active Concept Bottlenecks
Sonia Laguna, Katarzyna Kobalczyk, Julia E. Vogt +1
We introduce Concept Bottleneck Reward Models (CB-RM), a reward modeling framework that enables interpretable preference learning through selective concept annotation. Unlike stand…
Uncertainty Estimation for Trust Attribution to Speed-of-Sound Reconstruction with Variational Networks
Sonia Laguna, Lin Zhang, Can Deniz Bezek +4
Speed-of-sound (SoS) is a biomechanical characteristic of tissue, and its imaging can provide a promising biomarker for diagnosis. Reconstructing SoS images from ultrasound acquisi…
Text To 3D Object Generation For Scalable Room Assembly
Sonia Laguna, Alberto Garcia-Garcia, Marie-Julie Rakotosaona +3
Modern machine learning models for scene understanding, such as depth estimation and object tracking, rely on large, high-quality datasets that mimic real-world deployment scenario…
Beyond Glucose-Only Assessment: Advancing Nocturnal Hypoglycemia Prediction in Children with Type 1 Diabetes
Marco Voegeli, Sonia Laguna, Heike Leutheuser +3
The dead-in-bed syndrome describes the sudden and unexplained death of young individuals with Type 1 Diabetes (T1D) without prior long-term complications. One leading hypothesis at…
Measuring Leakage in Concept-Based Methods: An Information Theoretic Approach
Mikael Makonnen, Moritz Vandenhirtz, Sonia Laguna +1
Concept Bottleneck Models (CBMs) aim to enhance interpretability by structuring predictions around human-understandable concepts. However, unintended information leakage, where pre…