ML Anthology

Vinogradska, Julia

9 publications

TMLR 2025 Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning Under Partial Observability Carlos E. Luis, Alessandro Giacomo Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
AISTATS 2024 Scalable Meta-Learning with Gaussian Processes Petru Tighineanu, Lukas Grossberger, Paul Baireuther, Kathrin Skubch, Stefan Falkner, Julia Vinogradska, Felix Berkenkamp
JMLR 2024 Value-Distributional Model-Based Reinforcement Learning Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
AISTATS 2023 Model-Based Uncertainty in Value Functions Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
AISTATS 2022 Transfer Learning with Gaussian Processes for Bayesian Optimization Petru Tighineanu, Kathrin Skubch, Paul Baireuther, Attila Reiss, Felix Berkenkamp, Julia Vinogradska
NeurIPS 2022 Information-Theoretic Safe Exploration with Gaussian Processes Alessandro Bottero, Carlos Luis, Julia Vinogradska, Felix Berkenkamp, Jan R Peters
AISTATS 2020 Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization Lukas Fröhlich, Edgar Klenske, Julia Vinogradska, Christian Daniel, Melanie Zeilinger
JMLR 2017 Stability of Controllers for Gaussian Process Dynamics Julia Vinogradska, Bastian Bischoff, Duy Nguyen-Tuong, Jan Peters
ICML 2016 Stability of Controllers for Gaussian Process Forward Models Julia Vinogradska, Bastian Bischoff, Duy Nguyen-Tuong, Anne Romer, Henner Schmidt, Jan Peters