Nicholas Rhinehart

収録論文 21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

• QPILOTS: Efficient Test-Time Q-Steering for Flow Policies
  2026/6/11
• QPILOTS: Efficient Test-Time Q-Steering for Flow Policies
  2026/6/1
• OSCAR: Obstacle Survival Curves for Adaptive Robot Navigation
  2026/6/1
• UBP2: Uncertainty-Balanced Preference Planning for Efficient Preference-based Reinforcement Learning
  2026/6/1
• OccSim: Multi-kilometer Simulation with Long-horizon Occupancy World Models
  2026/3/1
• AutoWorld: Learning Multi-Agent Traffic Simulation with Self-Supervised World Models
  2026/3/1
• Ratatouille: Imitation Learning Ingredients for Real-world Social Robot Navigation
  2025/9/1
• Residual Reward Models for Preference-based Reinforcement Learning
  2025/7/1
• Towards foundational LiDAR world models with efficient latent flow matching
  2025/6/1
• DR-MPC: Deep Residual Model Predictive Control for Real-world Social Navigation
  2024/10/1
• Hybrid Imitative Planning with Geometric and Predictive Costs in Off-road Environments
  2021/11/1
• Rapid Exploration for Open-World Navigation with Latent Goal Models
  2021/4/1
• Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models
  2021/4/1
• ViNG: Learning Open-World Navigation with Visual Goals
  2020/12/1
• Parrot: Data-Driven Behavioral Priors for Reinforcement Learning
  2020/11/1
• Conservative Safety Critics for Exploration
  2020/10/1
• Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?
  2020/6/1
• Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting
  2020/3/1
• PRECOG: PREdiction Conditioned On Goals in Visual Multi-Agent Settings
  2019/5/1
• Deep Imitative Models for Flexible Inference, Planning, and Control
  2018/10/1
• Learning Neural Parsers with Deterministic Differentiable Imitation Learning
  2018/6/1