Falkner, Stefan

12 publications

ICML 2024 MALIBO: Meta-Learning for Likelihood-Free Bayesian Optimization Jiarong Pan, Stefan Falkner, Felix Berkenkamp, Joaquin Vanschoren

AISTATS 2024 Scalable Meta-Learning with Gaussian Processes Petru Tighineanu, Lukas Grossberger, Paul Baireuther, Kathrin Skubch, Stefan Falkner, Julia Vinogradska, Felix Berkenkamp

JMLR 2022 Auto-Sklearn 2.0: Hands-Free AutoML via Meta-Learning Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter

NeurIPS 2022 Trading Off Image Quality for Robustness Is Not Necessary with Regularized Deterministic Autoencoders Amrutha Saseendran, Kathrin Skubch, Stefan Falkner, Margret Keuper

NeurIPS 2021 Shape Your Space: A Gaussian Mixture Regularization Approach to Deterministic Autoencoders Amrutha Saseendran, Kathrin Skubch, Stefan Falkner, Margret Keuper

ICLR 2020 Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization Michael Volpp, Lukas P. Fröhlich, Kirsten Fischer, Andreas Doerr, Stefan Falkner, Frank Hutter, Christian Daniel

ICLR 2019 Learning to Design RNA Frederic Runge, Danny Stoll, Stefan Falkner, Frank Hutter

ECML-PKDD 2019 Optimizing Neural Networks for Patent Classification Louay Abdelgawad, Peter Kluegl, Erdan Genc, Stefan Falkner, Frank Hutter

ICML 2018 BOHB: Robust and Efficient Hyperparameter Optimization at Scale Stefan Falkner, Aaron Klein, Frank Hutter

AISTATS 2017 Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets Aaron Klein, Stefan Falkner, Simon Bartels, Philipp Hennig, Frank Hutter

ICLR 2017 Learning Curve Prediction with Bayesian Neural Networks Aaron Klein, Stefan Falkner, Jost Tobias Springenberg, Frank Hutter

NeurIPS 2016 Bayesian Optimization with Robust Bayesian Neural Networks Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter