2.2k citations · 5.4k across the 90 of their papers we have counts for
97 papers
Simulation-based Inference for Cardiovascular Models
Antoine Wehenkel, Laura Manduchi, Jens Behrmann +6
Over the past decades, hemodynamics simulators have steadily evolved and have become tools of choice for studying cardiovascular systems in-silico. While such tools are routinely u…
Robust Hybrid Learning With Expert Augmentation
Antoine Wehenkel, Jens Behrmann, Hsiang Hsu +3
Hybrid modelling reduces the misspecification of expert models by combining them with machine learning (ML) components learned from data. Similarly to many ML algorithms, hybrid mo…
Minimax Demographic Group Fairness in Federated Learning
Afroditi Papadaki, Natalia Martinez, Martin Bertran +2
Federated learning is an increasingly popular paradigm that enables a large number of entities to collaboratively learn better models. In this work, we study minimax group fairness…
Consistent Collaborative Filtering via Tensor Decomposition
Shiwen Zhao, Charles Crissman, Guillermo R Sapiro
Collaborative filtering is the de facto standard for analyzing users' activities and building recommendation systems for items. In this work we develop Sliced Anti-symmetric Decomp…
Distributionally Robust Group Backwards Compatibility
Martin Bertran, Natalia Martinez, Alex Oesterling +1
Machine learning models are updated as new data is acquired or new architectures are developed. These updates usually increase model performance, but may introduce backward compati…
Adversarial Factor Models for the Generation of Improved Autism Diagnostic Biomarkers
William E. Carson, Dmitry Isaev, Samatha Major +3
Discovering reliable measures that inform on autism spectrum disorder (ASD) diagnosis is critical for providing appropriate and timely treatment for this neurodevelopmental disorde…