متابعة
Imant Daunhawer
Imant Daunhawer
ETH Zurich, Kaiko.ai
بريد إلكتروني تم التحقق منه على ethz.ch
عنوان
عدد مرات الاقتباسات
عدد مرات الاقتباسات
السنة
Generalized Multimodal ELBO‏
TM Sutter*, I Daunhawer*, JE Vogt‏
International Conference on Learning Representations, 2021‏
1092021
Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence‏
TM Sutter, I Daunhawer, JE Vogt‏
Advances in Neural Information Processing Systems, 2020‏
892020
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
612020
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
532019
On the Limitations of Multimodal VAEs‏
I Daunhawer, TM Sutter, K Chin-Cheong, E Palumbo, JE Vogt‏
International Conference on Learning Representations, 2021‏
402021
Identifiability Results for Multimodal Contrastive Learning‏
I Daunhawer, A Bizeul, E Palumbo, A Marx, JE Vogt‏
International Conference on Learning Representations, 2023‏
382023
How robust is unsupervised representation learning to distribution shift?‏
Y Shi, I Daunhawer, JE Vogt, PHS Torr, A Sanyal‏
International Conference on Learning Representations, 2022‏
37*2022
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
332020
MMVAE+: Enhancing the generative quality of multimodal VAEs without compromises‏
E Palumbo, I Daunhawer, JE Vogt‏
International Conference on Learning Representations, 2023‏
282023
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
212021
Biases in the football betting market‏
I Daunhawer, D Schoch, S Kosub‏
Social Science Research Network, 2017‏
52017
Benchmarking the fairness of image upsampling methods‏
M Laszkiewicz, I Daunhawer, JE Vogt, A Fischer, J Lederer‏
ACM Conference on Fairness, Accountability, and Transparency, 489-517, 2024‏
42024
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
32021
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
32020
Validating the early phototherapy prediction tool across cohorts‏
I Daunhawer*, K Schumacher*, A Badura, JE Vogt, H Michel, S Wellmann‏
Frontiers in Pediatrics 11, 2023‏
12023
From Logits to Hierarchies: Hierarchical Clustering made Simple‏
E Palumbo, M Vandenhirtz, A Ryser, I Daunhawer, JE Vogt‏
arXiv preprint arXiv:2410.07858, 2024‏
2024
Benchmarking Self-Supervised Learning for Single-Cell Data‏
P Toma, O Ovcharenko, I Daunhawer, J Vogt, F Barkmann, V Boeva‏
bioRxiv, 2024.11. 04.620867, 2024‏
2024
Multimodal Representation Learning under Weak Supervision‏
I Daunhawer‏
ETH Zurich, 2023‏
2023
3DIdentBox: A Toolbox for Identifiability Benchmarking‏
A Bizeul, I Daunhawer, E Palumbo, B Schölkopf, A Marx, JE Vogt‏
Conference on Causal Learning and Reasoning, 2023‏
2023
Improving Multimodal Generative Models with Disentangled Latent Partitions‏
I Daunhawer, TM Sutter, JE Vogt‏
Bayesian Deep Learning workshop, NeurIPS 2019, 2019‏
2019
يتعذر على النظام إجراء العملية في الوقت الحالي. عاود المحاولة لاحقًا.
مقالات 1–20