68 citations · 213 across the 20 of their papers we have counts for
8 papers · 1 filter
M(otion)-mode Based Prediction of Ejection Fraction using Echocardiograms
Ece Ozkan, Thomas M. Sutter, Yurong Hu +2
Early detection of cardiac dysfunction through routine screening is vital for diagnosing cardiovascular diseases. An important metric of cardiac function is the left ventricular ej…
(Un)reasonable Allure of Ante-hoc Interpretability for High-stakes Domains: Transparency Is Necessary but Insufficient for Comprehensibility
Kacper Sokol, Julia E. Vogt
Ante-hoc interpretability has become the holy grail of explainable artificial intelligence for high-stakes domains such as healthcare; however, this notion is elusive, lacks a wide…
Beyond Normal: On the Evaluation of Mutual Information Estimators
Paweł Czyż, Frederic Grabowski, Julia E. Vogt +2
Mutual information is a general statistical dependency measure which has found applications in representation learning, causality, domain generalization and computational biology.…
Tree Variational Autoencoders
Laura Manduchi, Moritz Vandenhirtz, Alain Ryser +1
We propose Tree Variational Autoencoder (TreeVAE), a new generative hierarchical clustering model that learns a flexible tree-based posterior distribution over latent variables. Tr…
Signal Is Harder To Learn Than Bias: Debiasing with Focal Loss
Moritz Vandenhirtz, Laura Manduchi, Ričards Marcinkevičs +1
Spurious correlations are everywhere. While humans often do not perceive them, neural networks are notorious for learning unwanted associations, also known as biases, instead of th…
Differentiable Random Partition Models
Thomas M. Sutter, Alain Ryser, Joram Liebeskind +1
Partitioning a set of elements into an unknown number of mutually exclusive subsets is essential in many machine learning problems. However, assigning elements, such as samples in…