Thomas M. Sutter

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 18

Top Topics

Multimodal Information

Machine Learning Models

Jensen Shannon Divergence

Generative Model

Top Venues

Publications

Thomas M. Sutter, Yang Meng, Norbert Fortin, Julia E. Vogt, Stephan Mandt
Unity by Diversity: Improved Representation Learning in Multimodal VAEs. CoRR (2024)
Alain Ryser, Thomas M. Sutter, Alexander Marx, Julia E. Vogt
Anomaly Detection by Context Contrasting. CoRR (2024)
Thomas M. Sutter, Alain Ryser, Joram Liebeskind, Julia E. Vogt
Differentiable Random Partition Models. NeurIPS (2023)
Ece Ozkan, Thomas M. Sutter, Yurong Hu, Sebastian Balzer, Julia E. Vogt
M(otion)-Mode Based Prediction of Ejection Fraction Using Echocardiograms. DAGM (2023)
Thomas M. Sutter, Laura Manduchi, Alain Ryser, Julia E. Vogt
Learning Group Importance using the Differentiable Hypergeometric Distribution. ICLR (2023)
Ece Ozkan, Thomas M. Sutter, Yurong Hu, Sebastian Balzer, Julia E. Vogt
M(otion)-mode Based Prediction of Ejection Fraction using Echocardiograms. CoRR (2023)
Thomas M. Sutter, Alain Ryser, Joram Liebeskind, Julia E. Vogt
Differentiable Random Partition Models. CoRR (2023)
Imant Daunhawer, Thomas M. Sutter, Kieran Chin-Cheong, Emanuele Palumbo, Julia E. Vogt
On the Limitations of Multimodal VAEs. ICLR (2022)
Thomas M. Sutter, Laura Manduchi, Alain Ryser, Julia E. Vogt
Continuous Relaxation For The Multivariate Non-Central Hypergeometric Distribution. CoRR (2022)
Imant Daunhawer, Thomas M. Sutter, Kieran Chin-Cheong, Emanuele Palumbo, Julia E. Vogt
On the Limitations of Multimodal VAEs. CoRR (2021)
Thomas M. Sutter, Imant Daunhawer, Julia E. Vogt
Generalized Multimodal ELBO. ICLR (2021)
Thomas M. Sutter, Imant Daunhawer, Julia E. Vogt
Generalized Multimodal ELBO. CoRR (2021)
Thomas M. Sutter, Jan A. Roth, Kieran Chin-Cheong, Balthasar L. Hug, Julia E. Vogt
A comparison of general and disease-specific machine learning models for the prediction of unplanned hospital readmissions. J. Am. Medical Informatics Assoc. 28 (4) (2021)
Kieran Chin-Cheong, Thomas M. Sutter, Julia E. Vogt
Generation of Differentially Private Heterogeneous Electronic Health Records. CoRR (2020)
Thomas M. Sutter, Imant Daunhawer, Julia E. Vogt
Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence. CoRR (2020)
Imant Daunhawer, Thomas M. Sutter, Ricards Marcinkevics, Julia E. Vogt
Self-supervised Disentanglement of Modality-Specific and Shared Factors Improves Multimodal Generative Models. GCPR (2020)
Thomas M. Sutter, Imant Daunhawer, Julia E. Vogt
Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence. NeurIPS (2020)
Thomas M. Sutter, Imant Daunhawer, Julia E. Vogt
Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence. ViGIL@NeurIPS (2019)