Däubener, Sina

4 publications

UAI 2025 ELBO, Regularized Maximum Likelihood, and Their Common One-Sample Approximation for Training Stochastic Neural Networks Sina Däubener, Simon Damm, Asja Fischer

TMLR 2025 On the Challenges and Opportunities in Generative AI Laura Manduchi, Clara Meister, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin

ICMLW 2023 On the Limitations of Model Stealing with Uncertainty Quantification Models David Pape, Sina Däubener, Thorsten Eisenhofer, Antonio Emanuele Cinà, Lea Schönherr

NeurIPS 2022 How Sampling Impacts the Robustness of Stochastic Neural Networks Sina Däubener, Asja Fischer