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Stefan Bauer
Stefan Bauer
Helmholtz | TUM | CIFAR
Adresse e-mail validée de tum.de
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Année
Challenging common assumptions in the unsupervised learning of disentangled representations
F Locatello, S Bauer, M Lucic, G Raetsch, S Gelly, B Schölkopf, O Bachem
International Conference on Machine Learning (ICML) 2019, 2019
16762019
Toward causal representation learning
B Schölkopf, F Locatello, S Bauer, NR Ke, N Kalchbrenner, A Goyal, ...
Proceedings of the IEEE 109 (5), 612-634, 2021
14092021
Machine learning-enabled high-entropy alloy discovery
Z Rao, PY Tung, R Xie, Y Wei, H Zhang, A Ferrari, TPC Klaver, F Körmann, ...
Science, 2022
3712022
On the fairness of disentangled representations
F Locatello, G Abbati, T Rainforth, S Bauer, B Schölkopf, O Bachem
Neural Information Processing Systems (NeurIPS) 2019, 2019
2522019
Disentangling factors of variation using few labels
F Locatello, M Tschannen, S Bauer, G Rätsch, B Schölkopf, O Bachem
International Conference on Learning Representations (ICLR) 2020, 2019
2082019
Robustly disentangled causal mechanisms: Validating deep representations for interventional robustness
R Suter, D Miladinovic, B Schölkopf, S Bauer
International Conference on Machine Learning (ICML) 2019, 2019
2022019
Neural causal structure discovery from interventions
NR Ke, O Bilaniuk, A Goyal, S Bauer, H Larochelle, B Schölkopf, ...
Transactions on Machine Learning Research, 2023
194*2023
Automatic human sleep stage scoring using deep neural networks
A Malafeev, D Laptev, S Bauer, X Omlin, A Wierzbicka, A Wichniak, ...
Frontiers in neuroscience 12, 781, 2018
1642018
Learning counterfactual representations for estimating individual dose-response curves
P Schwab, L Linhardt, S Bauer, JM Buhmann, W Karlen
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5612-5619, 2020
1562020
On the transfer of inductive bias from simulation to the real world: a new disentanglement dataset
MW Gondal, M Wüthrich, Đ Miladinović, F Locatello, M Breidt, V Volchkov, ...
Neural Information Processing Systems (NeurIPS) 2019, 2019
1502019
Causalworld: A robotic manipulation benchmark for causal structure and transfer learning
O Ahmed, F Träuble, A Goyal, A Neitz, M Wüthrich, Y Bengio, B Schölkopf, ...
International Conference on Learning Representations (ICLR) 2021, 2020
1462020
On Disentangled Representations Learned From Correlated Data
F Träuble, E Creager, N Kilbertus, F Locatello, A Dittadi, A Goyal, ...
International Conference on Machine Learning (ICML), 2020
1402020
Bayesian Structure Learning with Generative Flow Networks
T Deleu, A Góis, C Emezue, M Rankawat, S Lacoste-Julien, S Bauer, ...
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
1352022
Diffusion models for video prediction and infilling
T Höppe, A Mehrjou, S Bauer, D Nielsen, A Dittadi
Transactions on Machine Learning Research (TMLR), 2022
1242022
Clinical predictive models for COVID-19: systematic study
P Schwab, ADM Schütte, B Dietz, S Bauer
Journal of medical Internet research 22 (10), e21439, 2020
1052020
On the Transfer of Disentangled Representations in Realistic Settings
A Dittadi, F Träuble, F Locatello, M Wüthrich, V Agrawal, O Winther, ...
International Conference on Learning Representations (ICLR) 2021, 2020
922020
Causal machine learning for predicting treatment outcomes
S Feuerriegel, D Frauen, V Melnychuk, J Schweisthal, K Hess, A Curth, ...
Nature Medicine 30 (4), 958-968, 2024
822024
Overcoming Barriers to Data Sharing with Medical Image Generation: A Comprehensive Evaluation
A DuMont Schütte, J Hetzel, S Gatidis, T Hepp, B Dietz, S Bauer, ...
npj Digital Medicine, 2020
772020
Multidimensional contrast limited adaptive histogram equalization
V Stimper, S Bauer, R Ernstorfer, B Schölkopf, RP Xian
IEEE Access 7, 165437-165447, 2019
762019
A sober look at the unsupervised learning of disentangled representations and their evaluation
F Locatello, S Bauer, M Lucic, G Rätsch, S Gelly, B Schölkopf, O Bachem
Journal of Machine Learning Research (JMLR), 2020
732020
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