Imant Daunhawer
Imant Daunhawer
PhD Student, ETH Zurich
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Enhanced early prediction of clinically relevant neonatal hyperbilirubinemia with machine learning
I Daunhawer, S Kasser, G Koch, L Sieber, H Cakal, J Tütsch, M Pfister, ...
Pediatric research 86 (1), 122-127, 2019
Pharmacometrics and machine learning partner to advance clinical data analysis
G Koch, M Pfister, I Daunhawer, M Wilbaux, S Wellmann, JE Vogt
Clinical Pharmacology & Therapeutics 107 (4), 926-933, 2020
Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence
TM Sutter, I Daunhawer, JE Vogt
Advances in Neural Information Processing Systems 33, 6100-6110, 2020
Generalized Multimodal ELBO
TM Sutter, I Daunhawer, JE Vogt
International Conference on Learning Representations, 2021
Self-supervised disentanglement of modality-specific and shared factors improves multimodal generative models
I Daunhawer, TM Sutter, R Marcinkevičs, JE Vogt
German Conference on Pattern Recognition, 459-473, 2020
Biases in the football betting market
I Daunhawer, D Schoch, S Kosub
SSRN, 2017
Machine learning used to compare the diagnostic accuracy of risk factors, clinical signs and biomarkers and to develop a new prediction model for neonatal early-onset sepsis
M Stocker, I Daunhawer, W Van Herk, S El Helou, S Dutta, ...
The Pediatric Infectious Disease Journal 41 (3), 248-254, 2021
On the Limitations of Multimodal VAEs
I Daunhawer, TM Sutter, K Chin-Cheong, E Palumbo, JE Vogt
International Conference on Learning Representations, 2021
How robust are pre-trained models to distribution shift?
Y Shi, I Daunhawer, JE Vogt, PHS Torr, A Sanyal
arXiv preprint arXiv:2206.08871, 2022
MMVAE+: Enhancing the Generative Quality of Multimodal VAEs without Compromises
E Palumbo, I Daunhawer, JE Vogt
ICLR Workshop on Deep Generative Models for Highly Structured Data, 2022
Decoupling State Representation Methods from Reinforcement Learning in Car Racing
JM Montoya, I Daunhawer, JE Vogt, MA Wiering
International Conference on Agents and Artificial Intelligence, 752-759, 2021
PET-guided Attention Network for Segmentation of Lung Tumors from PET/CT images
VK Pattisapu, I Daunhawer, T Weikert, A Sauter, B Stieltjes, JE Vogt
German Conference on Pattern Recognition, 445-458, 2020
Improving Multimodal Generative Models with Disentangled Latent Partitions
I Daunhawer, TM Sutter, JE Vogt
Bayesian Deep Learning workshop, NeurIPS 2019, 2019
Evolutionary algorithms for the discovery of trading rules in high-frequency betting markets
I Daunhawer
University of Konstanz, 2018
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Artigos 1–14