Scalable Safe Exploration for Global Optimization of Dynamical Systems. - Bhavya Sukhija; Matteo Turchetta; David Lindner; Andreas Krause 001; Sebastian Trimpe; Dominik Baumann (CoRR, 2022)

Trajectory Optimization Using Neural Network Gradients of Learned Dynamics. - Nathanael Köhler; Bhavya Sukhija; Miguel Zamora; Simon Zimmermann; Stelian Coros (CoRR, 2022)

Tuning Legged Locomotion Controllers via Safe Bayesian Optimization. - Daniel Widmer; Dongho Kang; Bhavya Sukhija; Jonas Hübotter; Andreas Krause 001; Stelian Coros (CoRL, 2023)

Gradient-Based Trajectory Optimization With Learned Dynamics. - Bhavya Sukhija; Nathanael Köhler; Miguel Zamora; Simon Zimmermann; Sebastian Curi; Andreas Krause 001; Stelian Coros (ICRA, 2023)

Optimistic Active Exploration of Dynamical Systems. - Bhavya Sukhija; Lenart Treven; Cansu Sancaktar; Sebastian Blaes; Stelian Coros; Andreas Krause 001 (NeurIPS, 2023)

Efficient Exploration in Continuous-time Model-based Reinforcement Learning. - Lenart Treven; Jonas Hübotter; Bhavya Sukhija; Florian Dörfler; Andreas Krause 001 (NeurIPS, 2023)

Hallucinated adversarial control for conservative offline policy evaluation. - Jonas Rothfuss; Bhavya Sukhija; Tobias Birchler; Parnian Kassraie; Andreas Krause 001 (UAI, 2023)

GoSafeOpt: Scalable safe exploration for global optimization of dynamical systems. - Bhavya Sukhija; Matteo Turchetta; David Lindner; Andreas Krause 001; Sebastian Trimpe; Dominik Baumann (Artif. Intell., 2023)

Bridging the Sim-to-Real Gap with Bayesian Inference. - Jonas Rothfuss; Bhavya Sukhija; Lenart Treven; Florian Dörfler; Stelian Coros; Andreas Krause 001 (IROS, 2024)

Transductive Active Learning: Theory and Applications. - Jonas Hübotter; Bhavya Sukhija; Lenart Treven; Yarden As; Andreas Krause 001 (NeurIPS, 2024)

NeoRL: Efficient Exploration for Nonepisodic RL. - Bhavya Sukhija; Lenart Treven; Florian Dörfler; Stelian Coros; Andreas Krause 001 (NeurIPS, 2024)

When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL. - Lenart Treven; Bhavya Sukhija; Yarden As; Florian Dörfler; Andreas Krause 001 (NeurIPS, 2024)

Active Few-Shot Fine-Tuning. - Jonas Hübotter; Bhavya Sukhija; Lenart Treven; Yarden As; Andreas Krause 001 (CoRR, 2024)

Information-based Transductive Active Learning. - Jonas Hübotter; Bhavya Sukhija; Lenart Treven; Yarden As; Andreas Krause 001 (CoRR, 2024)

Safe Exploration Using Bayesian World Models and Log-Barrier Optimization. - Yarden As; Bhavya Sukhija; Andreas Krause 001 (CoRR, 2024)

Meta-Reinforcement Learning for Universal Quadrupedal Locomotion Control. - Fabrizio Di Giuro; Fatemeh Zargarbashi; Jin Cheng 002; Dongho Kang; Bhavya Sukhija; Stelian Coros (CoRR, 2024)

Data-Efficient Task Generalization via Probabilistic Model-Based Meta Reinforcement Learning. - Arjun Bhardwaj; Jonas Rothfuss; Bhavya Sukhija; Yarden As; Marco Hutter 001; Stelian Coros; Andreas Krause 001 (IEEE Robotics Autom. Lett., 2024)

ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning. - Yarden As; Bhavya Sukhija; Lenart Treven; Carmelo Sferrazza; Stelian Coros; Andreas Krause 001 (ICLR, 2025)

MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization. - Bhavya Sukhija; Stelian Coros; Andreas Krause 001; Pieter Abbeel; Carmelo Sferrazza (ICLR, 2025)