Stefan Falkner

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 21

Top Topics

Top Venues

Publications

Petru Tighineanu, Lukas Grossberger, Paul Baireuther, Kathrin Skubch, Stefan Falkner, Julia Vinogradska, Felix Berkenkamp
Scalable Meta-Learning with Gaussian Processes. AISTATS (2024)
Jiarong Pan, Stefan Falkner, Felix Berkenkamp, Joaquin Vanschoren
MALIBO: Meta-learning for Likelihood-free Bayesian Optimization. CoRR (2023)
Petru Tighineanu, Lukas Grossberger, Paul Baireuther, Kathrin Skubch, Stefan Falkner, Julia Vinogradska, Felix Berkenkamp
Scalable Meta-Learning with Gaussian Processes. CoRR (2023)
Amrutha Saseendran, Kathrin Skubch, Stefan Falkner, Margret Keuper
Trading off Image Quality for Robustness is not Necessary with Regularized Deterministic Autoencoders. NeurIPS (2022)
Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning. J. Mach. Learn. Res. 23 (2022)
Amrutha Saseendran, Kathrin Skubch, Stefan Falkner, Margret Keuper
Shape your Space: A Gaussian Mixture Regularization Approach to Deterministic Autoencoders. NeurIPS (2021)
Michael Volpp, Lukas P. Fröhlich, Kirsten Fischer, Andreas Doerr, Stefan Falkner, Frank Hutter, Christian Daniel
Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization. ICLR (2020)
Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter
Auto-Sklearn 2.0: The Next Generation. CoRR (2020)
Louay Abdelgawad, Peter Kluegl, Erdan Genc, Stefan Falkner, Frank Hutter
Optimizing Neural Networks for Patent Classification. ECML/PKDD (3) (2019)
Frederic Runge, Danny Stoll, Stefan Falkner, Frank Hutter
Learning to Design RNA. ICLR (Poster) (2019)
Matilde Gargiani, Aaron Klein, Stefan Falkner, Frank Hutter
Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings. CoRR (2019)
Stefan Falkner, Aaron Klein, Frank Hutter
BOHB: Robust and Efficient Hyperparameter Optimization at Scale. ICML (2018)
Arber Zela, Aaron Klein, Stefan Falkner, Frank Hutter
Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search. CoRR (2018)
Stefan Falkner, Aaron Klein, Frank Hutter
Practical Hyperparameter Optimization for Deep Learning. ICLR (Workshop) (2018)
Stefan Falkner, Aaron Klein, Frank Hutter
BOHB: Robust and Efficient Hyperparameter Optimization at Scale. CoRR (2018)
Frederic Runge, Danny Stoll, Stefan Falkner, Frank Hutter
Learning to Design RNA. CoRR (2018)
Aaron Klein, Stefan Falkner, Jost Tobias Springenberg, Frank Hutter
Learning Curve Prediction with Bayesian Neural Networks. ICLR (Poster) (2017)
Aaron Klein, Stefan Falkner, Simon Bartels, Philipp Hennig, Frank Hutter
Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets. AISTATS (2017)
Aaron Klein, Stefan Falkner, Simon Bartels, Philipp Hennig, Frank Hutter
Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets. CoRR (2016)
Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter
Asynchronous Stochastic Gradient MCMC with Elastic Coupling. CoRR (2016)
Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter
Bayesian Optimization with Robust Bayesian Neural Networks. NIPS (2016)
Stefan Falkner, Marius Lindauer, Frank Hutter
SpySMAC: Automated Configuration and Performance Analysis of SAT Solvers. SAT (2015)