Anusha Nagabandi

収録論文 13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

• Support-Constrained RL Enables Real-World Policy Improvement without Real-World Experience
  2026/6/1
• TMRL: Diffusion Timestep-Modulated Pretraining Enables Exploration for Efficient Policy Finetuning
  2026/5/1
• RFS: Reinforcement Learning with Residual Flow Steering for Dexterous Manipulation
  2026/2/1
• Residual Off-Policy RL for Finetuning Behavior Cloning Policies
  2025/9/1
• Steering Your Diffusion Policy with Latent Space Reinforcement Learning
  2025/6/1
• Model-Based Reinforcement Learning via Latent-Space Collocation
  2021/6/1
• MELD: Meta-Reinforcement Learning from Images via Latent State Models
  2020/10/1
• Deep Dynamics Models for Learning Dexterous Manipulation
  2019/9/1
• Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL
  2018/12/1
• Learning to Adapt in Dynamic, Real-World Environments Through Meta-Reinforcement Learning
  2018/3/1
• Expressive Robot Motion Timing
  2018/2/1
• Learning Image-Conditioned Dynamics Models for Control of Under-actuated Legged Millirobots
  2017/11/1
• Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning
  2017/8/1