Thomas M. Sutter

According to our database, Thomas M. Sutter authored at least 29 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Beyond Independent Frames: Latent Attention Masked Autoencoders for Multi-View Echocardiography.

Simon Böhi, Irene Cannistraci, Sergio Muñoz Gonzalez, Moritz Vandenhirtz, Sonia Laguna, Samuel Ruipérez-Campillo, Max Krähenmann, Andrea Agostini, Ece Ozkan, Thomas M. Sutter, Julia E. Vogt

CoRR, April, 2026

Foundation Model for Cardiac Time Series via Masked Latent Attention.

Moritz Vandenhirtz, Samuel Ruipérez-Campillo, Simon Böhi, Sonia Laguna, Irene Cannistraci, Andrea Agostini, Ece Ozkan, Thomas M. Sutter, Julia E. Vogt

CoRR, March, 2026

Structure is Supervision: Multiview Masked Autoencoders for Radiology.

Sonia Laguna, Andrea Agostini, Alain Ryser, Samuel Ruipérez-Campillo, Irene Cannistraci, Moritz Vandenhirtz, Stephan Mandt, Nicolas Deperrois, Farhad Nooralahzadeh, Michael Krauthammer, Thomas M. Sutter, Julia E. Vogt

Trans. Mach. Learn. Res., 2026

Reducing diverse sources of noise in ventricular electrical signals using variational autoencoders.

Samuel Ruipérez-Campillo, Alain Ryser, Thomas M. Sutter, Brototo Deb, Ruibin Feng, Prasanth Ganesan, Kelly A. Brennan, Albert J. Rogers, Maarten Z. Kolk, Fleur V. Y. Tjong, Sanjiv M. Narayan, Julia E. Vogt

Expert Syst. Appl., 2026

2025

You Only Train Once: Differentiable Subset Selection for Omics Data.

Daphné Chopard, Jorge da Silva Goncalves, Irene Cannistraci, Thomas M. Sutter, Julia E. Vogt

CoRR, December, 2025

Enhancing Radiology Report Generation and Visual Grounding using Reinforcement Learning.

Benjamin Gundersen, Nicolas Deperrois, Samuel Ruipérez-Campillo, Thomas M. Sutter, Julia E. Vogt, Michael Moor, Farhad Nooralahzadeh, Michael Krauthammer

CoRR, December, 2025

Temporal Representation Learning for Real-Time Ultrasound Analysis.

Yves Stebler, Thomas M. Sutter, Ece Ozkan, Julia E. Vogt

CoRR, September, 2025

A Denoising VAE for Intracardiac Time Series in Ischemic Cardiomyopathy.

Samuel Ruipérez-Campillo, Alain Ryser, Thomas M. Sutter, Ruibin Feng, Prasanth Ganesan, Brototo Deb, Kelly A. Brennan, Maxime Pedron, Albert J. Rogers, Maarten Z. Kolk, Fleur V. Y. Tjong, Sanjiv M. Narayan, Julia E. Vogt

CoRR, July, 2025

Predicting Pulmonary Hypertension in Newborns: A Multi-view VAE Approach.

Lucas Erlacher, Samuel Ruipérez-Campillo, Holger Michel, Sven Wellmann, Thomas M. Sutter, Ece Ozkan, Julia E. Vogt

CoRR, July, 2025

Leveraging the Structure of Medical Data for Improved Representation Learning.

Andrea Agostini, Sonia Laguna, Alain Ryser, Samuel Ruipérez-Campillo, Moritz Vandenhirtz, Nicolas Deperrois, Farhad Nooralahzadeh, Michael Krauthammer, Thomas M. Sutter, Julia E. Vogt

CoRR, July, 2025

From Pixels to Components: Eigenvector Masking for Visual Representation Learning.

Alice Bizeul, Thomas M. Sutter, Alain Ryser, Bernhard Schölkopf, Julius von Kügelgen, Julia E. Vogt

CoRR, February, 2025

RadVLM: A Multitask Conversational Vision-Language Model for Radiology.

Nicolas Deperrois, Hidetoshi Matsuo, Samuel Ruipérez-Campillo, Moritz Vandenhirtz, Sonia Laguna, Alain Ryser, Koji Fujimoto, Mizuho Nishio, Thomas M. Sutter, Julia E. Vogt, Jonas Kluckert, Thomas Frauenfelder, Christian Blüthgen, Farhad Nooralahzadeh, Michael Krauthammer

CoRR, February, 2025

Two Is Better Than One: Aligned Representation Pairs for Anomaly Detection.

Alain Ryser, Thomas M. Sutter, Alexander Marx, Julia E. Vogt

Trans. Mach. Learn. Res., 2025

2024

Weakly-Supervised Multimodal Learning on MIMIC-CXR.

Andrea Agostini, Daphné Chopard, Yang Meng, Norbert Fortin, Babak Shahbaba, Stephan Mandt, Thomas M. Sutter, Julia E. Vogt

CoRR, 2024

Anomaly Detection by Context Contrasting.

Alain Ryser, Thomas M. Sutter, Alexander Marx, Julia E. Vogt

CoRR, 2024

Unity by Diversity: Improved Representation Learning in Multimodal VAEs.

Thomas M. Sutter, Yang Meng, Norbert Fortin, Julia E. Vogt, Stephan Mandt

CoRR, 2024

Unity by Diversity: Improved Representation Learning for Multimodal VAEs.

Thomas M. Sutter, Yang Meng, Andrea Agostini, Daphné Chopard, Norbert Fortin, Julia E. Vogt, Babak Shahbaba, Stephan Mandt

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Can Generative AI Learn Physiological Waveform Morphologies? A Study on Denoising Intracardiac Signals in Ischemic Cardiomyopathy.

Samuel Ruipérez-Campillo, Alain Ryser, Thomas M. Sutter, Ruibin Feng, Prasanth Ganesan, Brototo Deb, Kelly A. Brennan, Maarten Z. Kolk, Fleur V. Y. Tjong, Albert J. Rogers, Sanjiv M. Narayan, Julia E. Vogt

Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024

2023

Imposing and Uncovering Group Structure in Weakly-Supervised Learning.

Thomas M. Sutter

PhD thesis, 2023

Differentiable Random Partition Models.

Thomas M. Sutter, Alain Ryser, Joram Liebeskind, Julia E. Vogt

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Group Importance using the Differentiable Hypergeometric Distribution.

Thomas M. Sutter, Laura Manduchi, Alain Ryser, Julia E. Vogt

Proceedings of the Eleventh International Conference on Learning Representations, 2023

M(otion)-Mode Based Prediction of Ejection Fraction Using Echocardiograms.

Ece Ozkan, Thomas M. Sutter, Yurong Hu, Sebastian Balzer, Julia E. Vogt

Proceedings of the Pattern Recognition - 45th DAGM German Conference, 2023

2022

Continuous Relaxation For The Multivariate Non-Central Hypergeometric Distribution.

Thomas M. Sutter, Laura Manduchi, Alain Ryser, Julia E. Vogt

CoRR, 2022

On the Limitations of Multimodal VAEs.

Imant Daunhawer, Thomas M. Sutter, Kieran Chin-Cheong, Emanuele Palumbo, Julia E. Vogt

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

A comparison of general and disease-specific machine learning models for the prediction of unplanned hospital readmissions.

Thomas M. Sutter, Jan A. Roth, Kieran Chin-Cheong, Balthasar L. Hug, Julia E. Vogt

J. Am. Medical Informatics Assoc., 2021

Generalized Multimodal ELBO.

Thomas M. Sutter, Imant Daunhawer, Julia E. Vogt

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Generation of Differentially Private Heterogeneous Electronic Health Records.

Kieran Chin-Cheong, Thomas M. Sutter, Julia E. Vogt

CoRR, 2020

Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence.

Thomas M. Sutter, Imant Daunhawer, Julia E. Vogt

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Self-supervised Disentanglement of Modality-Specific and Shared Factors Improves Multimodal Generative Models.

Imant Daunhawer, Thomas M. Sutter, Ricards Marcinkevics, Julia E. Vogt

Proceedings of the Pattern Recognition - 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28, 2020