Daniel, Christian

13 publications

ICLR 2023 Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference Michael Volpp, Philipp Dahlinger, Philipp Becker, Christian Daniel, Gerhard Neumann

ICLR 2021 Bayesian Context Aggregation for Neural Processes Michael Volpp, Fabian Flürenbrock, Lukas Grossberger, Christian Daniel, Gerhard Neumann

ICML 2020 Differentiable Likelihoods for Fast Inversion of ’Likelihood-Free’ Dynamical Systems Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Tiemann, Philipp Hennig

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

AISTATS 2020 Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization Lukas Fröhlich, Edgar Klenske, Julia Vinogradska, Christian Daniel, Melanie Zeilinger

ICML 2019 Trajectory-Based Off-Policy Deep Reinforcement Learning Andreas Doerr, Michael Volpp, Marc Toussaint, Trimpe Sebastian, Christian Daniel

ICML 2018 Probabilistic Recurrent State-Space Models Andreas Doerr, Christian Daniel, Martin Schiegg, Nguyen-Tuong Duy, Stefan Schaal, Marc Toussaint, Trimpe Sebastian

CoRL 2017 Optimizing Long-Term Predictions for Model-Based Policy Search Andreas Doerr, Christian Daniel, Duy Nguyen-Tuong, Alonso Marco, Stefan Schaal, Marc Toussaint, Sebastian Trimpe

JMLR 2016 Hierarchical Relative Entropy Policy Search Christian Daniel, Gerhard Neumann, Oliver Kroemer, Jan Peters

AAAI 2016 Learning Step Size Controllers for Robust Neural Network Training Christian Daniel, Jonathan Taylor, Sebastian Nowozin

MLJ 2016 Probabilistic Inference for Determining Options in Reinforcement Learning Christian Daniel, Herke van Hoof, Jan Peters, Gerhard Neumann

NeurIPS 2013 Probabilistic Movement Primitives Alexandros Paraschos, Christian Daniel, Jan R Peters, Gerhard Neumann

AISTATS 2012 Hierarchical Relative Entropy Policy Search Christian Daniel, Gerhard Neumann, Jan Peters