Andreas Krause
収録論文 56本 ・ フィジカルAI/ロボット学習
※arXiv著者名で収集。同姓同名の別人の論文が含まれる場合があります。
論文
- Uncertainty Quantification for Flow-Based Vision-Language-Action Models2026/6/16
- Uncertainty Quantification for Flow-Based Vision-Language-Action Models2026/6/1
- Sampling-Based Safe Reinforcement Learning2026/5/1
- Bounded Ratio Reinforcement Learning2026/4/20
- Model-Based Reinforcement Learning for Control under Time-Varying Dynamics2026/4/1
- What Matters for Simulation to Online Reinforcement Learning on Real Robots2026/2/1
- Safe Exploration via Policy Priors2026/1/1
- Sample-efficient and Scalable Exploration in Continuous-Time RL2025/10/1
- TARC: Time-Adaptive Robotic Control2025/10/1
- Learning Soft Robotic Dynamics with Active Exploration2025/10/1
- Safe and Near-Optimal Control with Online Dynamics Learning2025/9/1
- SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer2025/9/1
- Robust-Sub-Gaussian Model Predictive Control for Safe Ultrasound-Image-Guided Robotic Spinal Surgery2025/8/1
- Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why2025/7/1
- SonoGym: High Performance Simulation for Challenging Surgical Tasks with Robotic Ultrasound2025/7/1
- DISCOVER: Automated Curricula for Sparse-Reward Reinforcement Learning2025/5/1
- Uncertainty-Aware Robotic World Model Makes Offline Model-Based Reinforcement Learning Work on Real Robots2025/4/23
- Uncertainty-Aware Robotic World Model Makes Offline Model-Based Reinforcement Learning Work on Real Robots2025/4/1
- NIL: No-data Imitation Learning by Leveraging Pre-trained Video Diffusion Models2025/3/13
- NIL: No-data Imitation Learning by Leveraging Pre-trained Video Diffusion Models2025/3/1
- Performance-driven Constrained Optimal Auto-Tuner for MPC2025/3/1
- Probabilistic Artificial Intelligence2025/2/7
- Symmetry-Guided Memory Augmentation for Efficient Locomotion Learning2025/2/3
- Symmetry-Guided Memory Augmentation for Efficient Locomotion Learning2025/2/1
- Robotic World Model: A Neural Network Simulator for Robust Policy Optimization in Robotics2025/1/1
- MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization2024/12/1
- Active Fine-Tuning of Multi-Task Policies2024/10/1
- ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning2024/10/1
- Bridging the Sim-to-Real Gap with Bayesian Inference2024/3/1
- Safe Guaranteed Exploration for Non-linear Systems2024/2/1
- Data-Efficient Task Generalization via Probabilistic Model-based Meta Reinforcement Learning2023/11/1
- Efficient Exploration in Continuous-time Model-based Reinforcement Learning2023/10/1
- Tuning Legged Locomotion Controllers via Safe Bayesian Optimization2023/6/1
- Safe Risk-averse Bayesian Optimization for Controller Tuning2023/6/1
- Optimistic Active Exploration of Dynamical Systems2023/6/1
- Safe Deep RL for Intraoperative Planning of Pedicle Screw Placement2023/5/1
- Leveraging Demonstrations with Latent Space Priors2022/10/1
- Near-Optimal Multi-Agent Learning for Safe Coverage Control2022/10/1
- Meta-Learning Priors for Safe Bayesian Optimization2022/10/1
- Gradient-Based Trajectory Optimization With Learned Dynamics2022/4/1
- Constrained Policy Optimization via Bayesian World Models2022/1/1
- Hierarchical Skills for Efficient Exploration2021/10/1
- Safe and Efficient Model-free Adaptive Control via Bayesian Optimization2021/1/1
- Safe Reinforcement Learning via Curriculum Induction2020/6/1
- Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning2020/6/1
- Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory2020/6/1
- Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization2019/10/1
- Safe Exploration for Interactive Machine Learning2019/10/1
- The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamical Systems2018/8/1
- Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Map-less Navigation by Leveraging Prior Demonstrations2018/5/1
- Learning-based Model Predictive Control for Safe Exploration2018/3/1
- Virtual vs. Real: Trading Off Simulations and Physical Experiments in Reinforcement Learning with Bayesian Optimization2017/3/1
- Safe Exploration in Finite Markov Decision Processes with Gaussian Processes2016/6/1
- Bayesian Optimization with Safety Constraints: Safe and Automatic Parameter Tuning in Robotics2016/2/1
- Safe Controller Optimization for Quadrotors with Gaussian Processes2015/9/1
- Efficient Informative Sensing using Multiple Robots2014/1/1