2025
scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data.
CoRR, June, 2025
From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection.
CoRR, May, 2025
Measuring Leakage in Concept-Based Methods: An Information Theoretic Approach.
CoRR, April, 2025
Beyond Glucose-Only Assessment: Advancing Nocturnal Hypoglycemia Prediction in Children with Type 1 Diabetes.
CoRR, April, 2025
Revisiting Automatic Data Curation for Vision Foundation Models in Digital Pathology.
,
,
,
,
,
,
,
,
,
,
,
,
,
,
CoRR, March, 2025
From Pixels to Components: Eigenvector Masking for Visual Representation Learning.
CoRR, February, 2025
RadVLM: A Multitask Conversational Vision-Language Model for Radiology.
,
,
,
,
,
,
,
,
,
,
,
,
,
,
CoRR, February, 2025
On the Properties and Estimation of Pointwise Mutual Information Profiles.
Trans. Mach. Learn. Res., 2025
Artificial intelligence should genuinely support clinical reasoning and decision making to bridge the translational gap.
npj Digit. Medicine, 2025
AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation.
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
J. Am. Medical Informatics Assoc., 2025
Cross-Entropy Is All You Need To Invert the Data Generating Process.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
2024
Deep Learning Based Prediction of Pulmonary Hypertension in Newborns Using Echocardiograms.
Int. J. Comput. Vis., July, 2024
Interpretable and intervenable ultrasonography-based machine learning models for pediatric appendicitis.
,
,
,
,
,
,
,
,
,
,
,
Medical Image Anal., January, 2024
Weakly-Supervised Multimodal Learning on MIMIC-CXR.
CoRR, 2024
Automatic Classification of General Movements in Newborns.
CoRR, 2024
Exploiting Interpretable Capabilities with Concept-Enhanced Diffusion and Prototype Networks.
CoRR, 2024
Hierarchical Clustering for Conditional Diffusion in Image Generation.
CoRR, 2024
From Logits to Hierarchies: Hierarchical Clustering made Simple.
CoRR, 2024
Structured Generations: Using Hierarchical Clusters to guide Diffusion Models.
CoRR, 2024
scTree: Discovering Cellular Hierarchies in the Presence of Batch Effects in scRNA-seq Data.
CoRR, 2024
Anomaly Detection by Context Contrasting.
CoRR, 2024
Unity by Diversity: Improved Representation Learning in Multimodal VAEs.
CoRR, 2024
On the Challenges and Opportunities in Generative AI.
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
CoRR, 2024
Stochastic Concept Bottleneck Models.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Unity by Diversity: Improved Representation Learning for Multimodal VAEs.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable?
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Benchmarking the Fairness of Image Upsampling Methods.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024
Can Generative AI Learn Physiological Waveform Morphologies? A Study on Denoising Intracardiac Signals in Ischemic Cardiomyopathy.
,
,
,
,
,
,
,
,
,
,
,
Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024
What Does Evaluation of Explainable Artificial Intelligence Actually Tell Us? A Case for Compositional and Contextual Validation of XAI Building Blocks.
Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 2024
2023
Interpretable and explainable machine learning: A methods-centric overview with concrete examples.
WIREs Data. Mining. Knowl. Discov., 2023
The Mixtures and the Neural Critics: On the Pointwise Mutual Information Profiles of Fine Distributions.
CoRR, 2023
(Un)reasonable Allure of Ante-hoc Interpretability for High-stakes Domains: Transparency Is Necessary but Insufficient for Explainability.
CoRR, 2023
Signal Is Harder To Learn Than Bias: Debiasing with Focal Loss.
CoRR, 2023
Differentiable Random Partition Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Tree Variational Autoencoders.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Effective Bayesian Heteroscedastic Regression with Deep Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Beyond Normal: On the Evaluation of Mutual Information Estimators.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
On the Identifiability and Estimation of Causal Location-Scale Noise Models.
Proceedings of the International Conference on Machine Learning, 2023
Breathing New Life into COPD Assessment: Multisensory Home-monitoring for Predicting Severity.
,
,
,
,
,
,
,
,
,
,
,
Proceedings of the 25th International Conference on Multimodal Interaction, 2023
Learning Group Importance using the Differentiable Hypergeometric Distribution.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
How robust is unsupervised representation learning to distribution shift?
Proceedings of the Eleventh International Conference on Learning Representations, 2023
MMVAE+: Enhancing the Generative Quality of Multimodal VAEs without Compromises.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Identifiability Results for Multimodal Contrastive Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
This Reads Like That: Deep Learning for Interpretable Natural Language Processing.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
M(otion)-Mode Based Prediction of Ejection Fraction Using Echocardiograms.
Proceedings of the Pattern Recognition - 45th DAGM German Conference, 2023
2022
Introduction to Machine Learning for Physicians: A Survival Guide for Data Deluge.
CoRR, 2022
Interpretable Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Models.
CoRR, 2022
How robust are pre-trained models to distribution shift?
CoRR, 2022
Continuous Relaxation For The Multivariate Non-Central Hypergeometric Distribution.
CoRR, 2022
Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Models.
Proceedings of the Machine Learning for Healthcare Conference, 2022
Debiasing Deep Chest X-Ray Classifiers using Intra- and Post-processing Methods.
Proceedings of the Machine Learning for Healthcare Conference, 2022
A Deep Variational Approach to Clustering Survival Data.
,
,
,
,
,
,
,
,
,
,
,
Proceedings of the Tenth International Conference on Learning Representations, 2022
On the Limitations of Multimodal VAEs.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Interpretable Prediction of Pulmonary Hypertension in Newborns Using Echocardiograms.
Proceedings of the Pattern Recognition, 2022
2021
A comparison of general and disease-specific machine learning models for the prediction of unplanned hospital readmissions.
J. Am. Medical Informatics Assoc., 2021
A Deep Variational Approach to Clustering Survival Data.
CoRR, 2021
Deep Conditional Gaussian Mixture Model for Constrained Clustering.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Learning Medical Risk Scores for Pediatric Appendicitis.
Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021
Generalized Multimodal ELBO.
Proceedings of the 9th International Conference on Learning Representations, 2021
Interpretable Models for Granger Causality Using Self-explaining Neural Networks.
Proceedings of the 9th International Conference on Learning Representations, 2021
Exploring Relationships between Cerebral and Peripheral Biosignals with Neural Networks.
Proceedings of the IEEE International Conference on Digital Health, 2021
Decoupling State Representation Methods from Reinforcement Learning in Car Racing.
Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021
T-DPSOM: an interpretable clustering method for unsupervised learning of patient health states.
Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021
2020
Interpretability and Explainability: A Machine Learning Zoo Mini-tour.
CoRR, 2020
Generation of Differentially Private Heterogeneous Electronic Health Records.
CoRR, 2020
Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
PET-Guided Attention Network for Segmentation of Lung Tumors from PET/CT Images.
Proceedings of the Pattern Recognition - 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28, 2020
Self-supervised Disentanglement of Modality-Specific and Shared Factors Improves Multimodal Generative Models.
Proceedings of the Pattern Recognition - 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28, 2020
2019
Unsupervised Extraction of Phenotypes from Cancer Clinical Notes for Association Studies.
CoRR, 2019
Bayesian Clustering for HIV1 Protease Inhibitor Contact Maps.
Proceedings of the Artificial Intelligence in Medicine, 2019
2015
Unsupervised Structure Detection in Biomedical Data.
IEEE ACM Trans. Comput. Biol. Bioinform., 2015
Probabilistic clustering of time-evolving distance data.
Mach. Learn., 2015
2013
Structure Preserving Embedding of Dissimilarity Data.
Proceedings of the Similarity-Based Pattern Analysis and Recognition, 2013
2012
A Complete Analysis of the l_1, p Group-Lasso.
Proceedings of the 29th International Conference on Machine Learning, 2012
Automatic Model Selection in Archetype Analysis.
Proceedings of the Pattern Recognition, 2012
2010
The Translation-invariant Wishart-Dirichlet Process for Clustering Distance Data.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010
The Group-Lasso: <i>l</i><sub>1, INFINITY</sub> Regularization versus <i>l</i><sub>1, 2</sub> Regularization.
Proceedings of the Pattern Recognition, 2010