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Julia Vinogradska
Julia Vinogradska
Bosch Center for Artificial Intelligence, Renningen
Verified email at de.bosch.com
Title
Cited by
Cited by
Year
Stability of Controllers for Gaussian Process Forward Models
J Vinogradska, B Bischoff, D Nguyen-Tuong, H Schmidt, A Romer, ...
Proceedings of The 33rd International Conference on Machine Learning, 545-554, 2016
522016
Transfer learning with gaussian processes for bayesian optimization
P Tighineanu, K Skubch, P Baireuther, A Reiss, F Berkenkamp, ...
International Conference on Artificial Intelligence and Statistics, 6152-6181, 2022
362022
Noisy-input entropy search for efficient robust Bayesian optimization
L Fröhlich, E Klenske, J Vinogradska, C Daniel, M Zeilinger
International Conference on Artificial Intelligence and Statistics, 2262-2272, 2020
342020
Stability of controllers for Gaussian process dynamics
J Vinogradska, B Bischoff, D Nguyen-Tuong, J Peters
Journal of Machine Learning Research 18 (100), 1-37, 2017
262017
Numerical quadrature for probabilistic policy search
J Vinogradska, B Bischoff, J Achterhold, T Koller, J Peters
IEEE transactions on pattern analysis and machine intelligence 42 (1), 164-175, 2018
152018
Model-based uncertainty in value functions
CE Luis, AG Bottero, J Vinogradska, F Berkenkamp, J Peters
International Conference on Artificial Intelligence and Statistics, 8029-8052, 2023
102023
Information-theoretic safe exploration with Gaussian processes
A Bottero, C Luis, J Vinogradska, F Berkenkamp, JR Peters
Advances in Neural Information Processing Systems 35, 30707-30719, 2022
82022
Value-Distributional Model-Based Reinforcement Learning
CE Luis, AG Bottero, J Vinogradska, F Berkenkamp, J Peters
Journal of Machine Learning Research 25 (298), 1-42, 2024
32024
Approximate value iteration based on numerical quadrature
J Vinogradska, B Bischoff, J Peters
IEEE Robotics and Automation Letters 3 (2), 1330-1337, 2018
32018
Gaussian processes in reinforcement learning: Stability analysis and efficient value propagation
J Vinogradska
Technische Universität Darmstadt, 2018
32018
Scalable Meta-Learning with Gaussian Processes
P Tighineanu, L Grossberger, P Baireuther, K Skubch, S Falkner, ...
International Conference on Artificial Intelligence and Statistics, 1981-1989, 2024
22024
Information-Theoretic Safe Bayesian Optimization
AG Bottero, CE Luis, J Vinogradska, F Berkenkamp, J Peters
arXiv preprint arXiv:2402.15347, 2024
22024
Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning under Partial Observability
CE Luis, AG Bottero, J Vinogradska, F Berkenkamp, J Peters
arXiv preprint arXiv:2409.16824, 2024
2024
Device and method for controlling a robot
AG Bottero, CEL Goncalves, F Berkenkamp, J Peters, J Vinogradska
US Patent App. 18/508,104, 2024
2024
Dynamics model for globally stable modeling of system dynamics
G Manek, JZ Kolter, J Vinogradska
US Patent 11,886,782, 2024
2024
Constrained controlling of a computer-controlled system
AG Bottero, CEL Goncalves, F Berkenkamp, J Peters, J Vinogradska
US Patent App. 18/331,751, 2024
2024
Model-Based Epistemic Variance of Values for Risk-Aware Policy Optimization
CE Luis, AG Bottero, J Vinogradska, F Berkenkamp, J Peters
arXiv preprint arXiv:2312.04386, 2023
2023
Method and device for setting at least one parameter of an actuator control system, actuator control system and data set
B Bischoff, J Vinogradska, J Peters
US Patent 11,669,070, 2023
2023
System, device, and method for controlling a physical or chemical process
P Tighineanu, A Reiss, F Berkenkamp, J Vinogradska, K Skubch, ...
US Patent App. 17/950,542, 2023
2023
Method and device for setting at least one parameter of an actuator control system and actuator control system
B Bischoff, J Vinogradska, J Peters
US Patent 11,550,272, 2023
2023
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