Franziska Meier

収録論文 36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

• DREAMSTEER: Latent World Models Can Steer VLA Policies During Deployment Without Any Finetuning
  2026/7/1
• Visuo-Tactile World Models
  2026/2/1
• WorldPlanner: Monte Carlo Tree Search and MPC with Action-Conditioned Visual World Models
  2025/11/1
• V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning
  2025/6/1
• Locate 3D: Real-World Object Localization via Self-Supervised Learning in 3D
  2025/4/1
• Unifying 2D and 3D Vision-Language Understanding
  2025/3/1
• Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass
  2025/1/1
• What do we learn from a large-scale study of pre-trained visual representations in sim and real environments?
  2023/10/1
• Neural Constraint Satisfaction: Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement
  2023/3/1
• Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?
  2023/3/1
• Cross-Domain Transfer via Semantic Skill Imitation
  2022/12/1
• Neural Grasp Distance Fields for Robot Manipulation
  2022/11/1
• Differentiable and Learnable Robot Models
  2022/2/1
• Learning Time-Invariant Reward Functions through Model-Based Inverse Reinforcement Learning
  2021/7/1
• Habitat 2.0: Training Home Assistants to Rearrange their Habitat
  2021/6/1
• Leveraging Forward Model Prediction Error for Learning Control
  2020/11/1
• Multi-Modal Learning of Keypoint Predictive Models for Visual Object Manipulation
  2020/11/1
• Learning Navigation Skills for Legged Robots with Learned Robot Embeddings
  2020/11/1
• Model-Based Inverse Reinforcement Learning from Visual Demonstrations
  2020/10/1
• Residual Learning from Demonstration: Adapting DMPs for Contact-rich Manipulation
  2020/8/1
• Planning in Learned Latent Action Spaces for Generalizable Legged Locomotion
  2020/8/1
• Supervised Learning and Reinforcement Learning of Feedback Models for Reactive Behaviors: Tactile Feedback Testbed
  2020/7/1
• Learning State-Dependent Losses for Inverse Dynamics Learning
  2020/3/1
• Encoding Physical Constraints in Differentiable Newton-Euler Algorithm
  2020/1/1
• Learning Generalizable Locomotion Skills with Hierarchical Reinforcement Learning
  2019/9/1
• Meta-Learning via Learned Loss
  2019/6/1
• Curious iLQR: Resolving Uncertainty in Model-based RL
  2019/4/1
• Using Simulation to Improve Sample-Efficiency of Bayesian Optimization for Bipedal Robots
  2018/5/1
• SE3-Pose-Nets: Structured Deep Dynamics Models for Visuomotor Planning and Control
  2017/10/1
• Learning Sensor Feedback Models from Demonstrations via Phase-Modulated Neural Networks
  2017/10/1
• A New Data Source for Inverse Dynamics Learning
  2017/10/1
• Real-time Perception meets Reactive Motion Generation
  2017/3/1
• A Probabilistic Representation for Dynamic Movement Primitives
  2016/12/1
• Learning Feedback Terms for Reactive Planning and Control
  2016/10/1
• DOOMED: Direct Online Optimization of Modeling Errors in Dynamics
  2016/8/1
• Local Gaussian Regression
  2014/2/1