Julia Vinogradska

21 papers A* 2A 4Journal 14

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning under Partial Observability. Trans. Mach. Learn. Res. Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
2024	J	`jnl`	Information-Theoretic Safe Bayesian Optimization. CoRR Alessandro G. Bottero, Carlos E. Luis, Julia Vinogradska, Felix Berkenkamp, Jan Peters
2024	A	`conf`	Scalable Meta-Learning with Gaussian Processes. AISTATS Petru Tighineanu, Lukas Grossberger, Paul Baireuther, Kathrin Skubch, Stefan Falkner, Julia Vinogradska, Felix Berkenkamp
2024	J	`jnl`	Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning under Partial Observability. CoRR Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
2024	J	`jnl`	Value-Distributional Model-Based Reinforcement Learning. J. Mach. Learn. Res. Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
2023	J	`jnl`	Model-Based Epistemic Variance of Values for Risk-Aware Policy Optimization. CoRR Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
2023	A	`conf`	Model-Based Uncertainty in Value Functions. AISTATS Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
2023	J	`jnl`	Model-Based Uncertainty in Value Functions. CoRR Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
2023	J	`jnl`	Scalable Meta-Learning with Gaussian Processes. CoRR Petru Tighineanu, Lukas Grossberger, Paul Baireuther, Kathrin Skubch, Stefan Falkner, Julia Vinogradska, Felix Berkenkamp
2023	J	`jnl`	Value-Distributional Model-Based Reinforcement Learning. CoRR Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
2022	A*	`conf`	Information-Theoretic Safe Exploration with Gaussian Processes. NeurIPS Alessandro G. Bottero, Carlos E. Luis, Julia Vinogradska, Felix Berkenkamp, Jan Peters
2022	J	`jnl`	Information-Theoretic Safe Exploration with Gaussian Processes. CoRR Alessandro G. Bottero, Carlos E. Luis, Julia Vinogradska, Felix Berkenkamp, Jan Peters
2022	A	`conf`	Transfer Learning with Gaussian Processes for Bayesian Optimization. AISTATS Petru Tighineanu, Kathrin Skubch, Paul Baireuther, Attila Reiss, Felix Berkenkamp, Julia Vinogradska
2021	J	`jnl`	Transfer Learning with Gaussian Processes for Bayesian Optimization. CoRR Petru Tighineanu, Kathrin Skubch, Paul Baireuther, Attila Reiss, Felix Berkenkamp, Julia Vinogradska
2020	A	`conf`	Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization. AISTATS Lukas P. Fröhlich, Edgar D. Klenske, Julia Vinogradska, Christian Daniel, Melanie N. Zeilinger
2020	J	`jnl`	Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization. CoRR Lukas P. Fröhlich, Edgar D. Klenske, Julia Vinogradska, Christian Daniel, Melanie N. Zeilinger
2020	J	`jnl`	Numerical Quadrature for Probabilistic Policy Search. IEEE Trans. Pattern Anal. Mach. Intell. Julia Vinogradska, Bastian Bischoff, Jan Achterhold, Torsten Koller, Jan Peters
2018	J	`jnl`	Approximate Value Iteration Based on Numerical Quadrature. IEEE Robotics Autom. Lett. Julia Vinogradska, Bastian Bischoff, Jan Peters
2018	—	`—`	Gaussian Processes in Reinforcement Learning: Stability Analysis and Efficient Value Propagation. Julia Vinogradska
2017	J	`jnl`	Stability of Controllers for Gaussian Process Dynamics. J. Mach. Learn. Res. Julia Vinogradska, Bastian Bischoff, Duy Nguyen-Tuong, Jan Peters
2016	A*	`conf`	Stability of Controllers for Gaussian Process Forward Models. ICML Julia Vinogradska, Bastian Bischoff, Duy Nguyen-Tuong, Anne Romer, Henner Schmidt, Jan Peters