Author of the publication

Challenges and Perspectives in Deep Generative Modeling (Dagstuhl Seminar 23072).

, , , , and . Dagstuhl Reports, 13 (2): 47-70 (February 2023)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

 

Other publications of authors with the same name

On the Choice of Priors in Bayesian Deep Learning.. ETH Zurich, Zürich, Switzerland, (2021)base-search.net (ftethz:oai:www.research-collection.ethz.ch:20.500.11850/523269).Priors in Bayesian Deep Learning: A Review.. CoRR, (2021)Neural Variational Gradient Descent., , and . CoRR, (2021)Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations., , , , and . NeurIPS, (2022)Conservative Uncertainty Estimation By Fitting Prior Networks., , , , and . ICLR, OpenReview.net, (2020)Towards Dynamic Feature Acquisition on Medical Time Series by Maximizing Conditional Mutual Information., , , and . CoRR, (2024)Challenges and Perspectives in Deep Generative Modeling (Dagstuhl Seminar 23072)., , , , and . Dagstuhl Reports, 13 (2): 47-70 (February 2023)Repulsive Deep Ensembles are Bayesian., and . NeurIPS, page 3451-3465. (2021)PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees., , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 9116-9126. PMLR, (2021)GP-VAE: Deep Probabilistic Time Series Imputation., , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 1651-1661. PMLR, (2020)