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Thomas M. Sutter
Thomas M. Sutter
Postdoc, ETH Zurich
Bestätigte E-Mail-Adresse bei inf.ethz.ch - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Generalized multimodal ELBO
TM Sutter, I Daunhawer, JE Vogt
arXiv preprint arXiv:2105.02470, 2021
682021
Multimodal Learning Utilizing Jensen-Shannon Divergence
TM Sutter, I Daunhawer, JE Vogt
Advances in Neural Information Processing Systems 33 pre-proceedings …, 2020
63*2020
Generation of Heterogeneous Synthetic Electronic Health Records using GANs
K Chin-Cheong, TM Sutter, JE Vogt
Workshop on Machine Learning for Health (ML4H) at the 33rd Conference on …, 2019
262019
On the limitations of multimodal vaes
I Daunhawer, TM Sutter, K Chin-Cheong, E Palumbo, JE Vogt
arXiv preprint arXiv:2110.04121, 2021
252021
Self-supervised disentanglement of modality-specific and shared factors improves multimodal generative models
I Daunhawer, TM Sutter, R Marcinkevičs, JE Vogt
Pattern Recognition: 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen …, 2021
242021
Machine learning algorithms evaluate immune response to novel Mycobacterium tuberculosis antigens for diagnosis of tuberculosis
NR Meier, N Ritz, TM Sutter, JE Vogt, THM Ottenhoff, M Jacobsen
Frontiers in Cellular and Infection Microbiology 10, 821, 2020
122020
A comparison of general and disease-specific machine learning models for the prediction of unplanned hospital readmissions
TM Sutter, JA Roth, K Chin-Cheong, BL Hug, JE Vogt
Journal of the American Medical Informatics Association, 2020
92020
Camera based visibility estimation
T Sutter, F Nater, C Sigg
Proceedings of the WMO Technical Conference on Meteorological and …, 2016
82016
Learning Group Importance using the Differentiable Hypergeometric Distribution
TM Sutter, L Manduchi, A Ryser, JE Vogt
The Eleventh International Conference on Learning Representations, 2023
62023
Generation of differentially private heterogeneous electronic health records
K Chin-Cheong, T Sutter, JE Vogt
arXiv preprint arXiv:2006.03423, 2020
62020
Generation of Heterogeneous Synthetic Electronic Health Records using GANs. ETH Zurich
K Chin-Cheong, T Sutter, JE Vogt
Institute for Machine Learning, 2019
62019
Differentiable Random Partition Models
TM Sutter, A Ryser, J Liebeskind, JE Vogt
arXiv preprint arXiv:2305.16841, 2023
22023
M (otion)-mode Based Prediction of Cardiac Function on Echocardiograms
TM Sutter, S Balzer, E Oezkan, JE Vogt
ETH Zurich, 2022
22022
Multimodal Relational VAE
TM Sutter, JE Vogt
Neurips Workshop on Bayesian Deep Learning, 2021
22021
Unity by Diversity: Improved Representation Learning in Multimodal VAEs
TM Sutter, Y Meng, N Fortin, JE Vogt, S Mandt
arXiv preprint arXiv:2403.05300, 2024
2024
Vector-based feedback of continuous wave radiofrequency compression cavity for ultrafast electron diffraction
TM Sutter, JSH Lee, AV Kulkarni, P Musumeci, A Kogar
Structural Dynamics 11 (2), 2024
2024
Differentiable Set Partitioning
TM Sutter, A Ryser, J Liebeskind, JE Vogt
ICML 2023 Workshop on Differentiable Almost Everything: Differentiable …, 2023
2023
M (otion)-mode Based Prediction of Ejection Fraction using Echocardiograms
E Ozkan, TM Sutter, Y Hu, S Balzer, JE Vogt
arXiv preprint arXiv:2309.03759, 2023
2023
Uncovering Latent Structure Using Random Partition Models
TM Sutter, A Ryser, J Liebeskind, JE Vogt
2023
Variational Partitioning
TM Sutter, A Ryser, J Liebeskind, JE Vogt
Fifth Symposium on Advances in Approximate Bayesian Inference, 2023
2023
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