Thomas M. Sutter

35 papers A* 6Journal 24Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Foundation Model for Cardiac Time Series via Masked Latent Attention. CoRR Moritz Vandenhirtz, Samuel Ruipérez-Campillo, Simon Böhi, Sonia Laguna, Irene Cannistraci, Andrea Agostini, Ece Ozkan, Thomas M. Sutter, Julia E. Vogt
2026	J	`jnl`	Reducing diverse sources of noise in ventricular electrical signals using variational autoencoders. Expert Syst. Appl. 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
2026	J	`jnl`	Structure is Supervision: Multiview Masked Autoencoders for Radiology. Trans. Mach. Learn. Res. 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
2025	J	`jnl`	A Denoising VAE for Intracardiac Time Series in Ischemic Cardiomyopathy. CoRR 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
2025	J	`jnl`	Enhancing Radiology Report Generation and Visual Grounding using Reinforcement Learning. CoRR Benjamin Gundersen, Nicolas Deperrois, Samuel Ruipérez-Campillo, Thomas M. Sutter, Julia E. Vogt, Michael Moor, Farhad Nooralahzadeh, Michael Krauthammer
2025	J	`jnl`	From Pixels to Components: Eigenvector Masking for Visual Representation Learning. CoRR Alice Bizeul, Thomas M. Sutter, Alain Ryser, Bernhard Schölkopf, Julius von Kügelgen, Julia E. Vogt
2025	J	`jnl`	Leveraging the Structure of Medical Data for Improved Representation Learning. CoRR Andrea Agostini, Sonia Laguna, Alain Ryser, Samuel Ruipérez-Campillo, Moritz Vandenhirtz, Nicolas Deperrois, Farhad Nooralahzadeh, Michael Krauthammer, Thomas M. Sutter, Julia E. Vogt
2025	J	`jnl`	Predicting Pulmonary Hypertension in Newborns: A Multi-view VAE Approach. CoRR Lucas Erlacher, Samuel Ruipérez-Campillo, Holger Michel, Sven Wellmann, Thomas M. Sutter, Ece Ozkan, Julia E. Vogt
2025	J	`jnl`	RadVLM: A Multitask Conversational Vision-Language Model for Radiology. CoRR 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
2025	J	`jnl`	Structure is Supervision: Multiview Masked Autoencoders for Radiology. CoRR 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
2025	J	`jnl`	Temporal Representation Learning for Real-Time Ultrasound Analysis. CoRR Yves Stebler, Thomas M. Sutter, Ece Ozkan, Julia E. Vogt
2025	J	`jnl`	Two Is Better Than One: Aligned Representation Pairs for Anomaly Detection. Trans. Mach. Learn. Res. Alain Ryser, Thomas M. Sutter, Alexander Marx, Julia E. Vogt
2025	J	`jnl`	You Only Train Once: Differentiable Subset Selection for Omics Data. CoRR Daphné Chopard, Jorge da Silva Goncalves, Irene Cannistraci, Thomas M. Sutter, Julia E. Vogt
2024	J	`jnl`	Anomaly Detection by Context Contrasting. CoRR Alain Ryser, Thomas M. Sutter, Alexander Marx, Julia E. Vogt
2024	—	`conf`	Can Generative AI Learn Physiological Waveform Morphologies? A Study on Denoising Intracardiac Signals in Ischemic Cardiomyopathy. EMBC 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
2024	A*	`conf`	Unity by Diversity: Improved Representation Learning for Multimodal VAEs. NeurIPS Thomas M. Sutter, Yang Meng, Andrea Agostini, Daphné Chopard, Norbert Fortin, Julia E. Vogt, Babak Shahbaba, Stephan Mandt
2024	J	`jnl`	Unity by Diversity: Improved Representation Learning in Multimodal VAEs. CoRR Thomas M. Sutter, Yang Meng, Norbert Fortin, Julia E. Vogt, Stephan Mandt
2024	J	`jnl`	Weakly-Supervised Multimodal Learning on MIMIC-CXR. CoRR Andrea Agostini, Daphné Chopard, Yang Meng, Norbert Fortin, Babak Shahbaba, Stephan Mandt, Thomas M. Sutter, Julia E. Vogt
2023	A*	`conf`	Differentiable Random Partition Models. NeurIPS Thomas M. Sutter, Alain Ryser, Joram Liebeskind, Julia E. Vogt
2023	J	`jnl`	Differentiable Random Partition Models. CoRR Thomas M. Sutter, Alain Ryser, Joram Liebeskind, Julia E. Vogt
2023	—	`—`	Imposing and Uncovering Group Structure in Weakly-Supervised Learning. Thomas M. Sutter
2023	A*	`conf`	Learning Group Importance using the Differentiable Hypergeometric Distribution. ICLR Thomas M. Sutter, Laura Manduchi, Alain Ryser, Julia E. Vogt
2023	—	`conf`	M(otion)-Mode Based Prediction of Ejection Fraction Using Echocardiograms. DAGM Ece Ozkan, Thomas M. Sutter, Yurong Hu, Sebastian Balzer, Julia E. Vogt
2023	J	`jnl`	M(otion)-mode Based Prediction of Ejection Fraction using Echocardiograms. CoRR Ece Ozkan, Thomas M. Sutter, Yurong Hu, Sebastian Balzer, Julia E. Vogt
2022	J	`jnl`	Continuous Relaxation For The Multivariate Non-Central Hypergeometric Distribution. CoRR Thomas M. Sutter, Laura Manduchi, Alain Ryser, Julia E. Vogt
2022	A*	`conf`	On the Limitations of Multimodal VAEs. ICLR Imant Daunhawer, Thomas M. Sutter, Kieran Chin-Cheong, Emanuele Palumbo, Julia E. Vogt
2021	J	`jnl`	A comparison of general and disease-specific machine learning models for the prediction of unplanned hospital readmissions. J. Am. Medical Informatics Assoc. Thomas M. Sutter, Jan A. Roth, Kieran Chin-Cheong, Balthasar L. Hug, Julia E. Vogt
2021	A*	`conf`	Generalized Multimodal ELBO. ICLR Thomas M. Sutter, Imant Daunhawer, Julia E. Vogt
2021	J	`jnl`	Generalized Multimodal ELBO. CoRR Thomas M. Sutter, Imant Daunhawer, Julia E. Vogt
2021	J	`jnl`	On the Limitations of Multimodal VAEs. CoRR Imant Daunhawer, Thomas M. Sutter, Kieran Chin-Cheong, Emanuele Palumbo, Julia E. Vogt
2020	J	`jnl`	Generation of Differentially Private Heterogeneous Electronic Health Records. CoRR Kieran Chin-Cheong, Thomas M. Sutter, Julia E. Vogt
2020	A*	`conf`	Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence. NeurIPS Thomas M. Sutter, Imant Daunhawer, Julia E. Vogt
2020	J	`jnl`	Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence. CoRR Thomas M. Sutter, Imant Daunhawer, Julia E. Vogt
2020	—	`conf`	Self-supervised Disentanglement of Modality-Specific and Shared Factors Improves Multimodal Generative Models. GCPR Imant Daunhawer, Thomas M. Sutter, Ricards Marcinkevics, Julia E. Vogt
2019	—	`conf`	Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence. ViGIL@NeurIPS Thomas M. Sutter, Imant Daunhawer, Julia E. Vogt