Tuesday
Table of contents
- A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects
- ACNMP: Skill Transfer and Task Extrapolation through Learning from Demonstration and Reinforcement Learning via Representation Sharing
- Action-based Representation Learning for Autonomous Driving
- Assisted Perception: Optimizing Observations to Communicate State
- Attention-Privileged Reinforcement Learning
- Attentional Separation-and-Aggregation Network for Self-supervised Depth-Pose Learning in Dynamic Scenes
- BayesRace: Learning to race autonomously using prior experience
- CAMPs: Learning Context-Specific Abstractions for Efficient Planning in Factored MDPs
- DIRL: Domain-Invariant Representation Learning for Sim-to-Real Transfer
- DROGON: A Trajectory Prediction Model based on Intention-Conditioned Behavior Reasoning
- Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control
- DeepMPCVS: Deep Model Predictive Control for Visual Servoing
- EXI-Net: EXplicitly/Implicitly Conditioned Network for Multiple Environment Sim-to-Real Transfer
- Flightmare: A Flexible Quadrotor Simulator
- From pixels to legs: Hierarchical learning of quadruped locomotion
- GDN: A Coarse-To-Fine (C2F) Representation for End-To-End 6-DoF Grasp Detection
- Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions
- Incremental learning of EMG-based control commands using Gaussian Processes
- Interactive Imitation Learning in State-Space
- Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting
- Iterative Semi-parametric Dynamics Model Learning For Autonomous Racing
- Learning 3D Dynamic Scene Representations for Robot Manipulation
- Learning Certified Control Using Contraction Metric
- Learning Dexterous Manipulation from Suboptimal Experts
- Learning Equality Constraints for Motion Planning on Manifolds
- Learning Hierarchical Task Networks with Preferences from Unannotated Demonstrations
- Learning Hybrid Control Barrier Functions from Data
- Learning Latent Representations to Influence Multi-Agent Interaction
- Learning Obstacle Representations for Neural Motion Planning
- Learning Stability Certificates from Data
- Learning Vision-based Reactive Policies for Obstacle Avoidance
- Learning from Suboptimal Demonstration via Self-Supervised Reward Regression
- Learning hierarchical relationships for object-goal navigation
- Learning to Improve Multi-Robot Hallway Navigation
- Learning to Walk in the Real World with Minimal Human Effort
- LiRaNet: End-to-End Trajectory Prediction using Spatio-Temporal Radar Fusion
- MATS: An Interpretable Trajectory Forecasting Representation for Planning and Control
- Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments
- Multi-Level Structure vs. End-to-End-Learning in High-Performance Tactile Robotic Manipulation
- MultiPoint: Cross-spectral registration of thermal and optical aerial imagery
- One Thousand and One Hours: Self-driving Motion Prediction Dataset
- PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards
- Positive-Unlabeled Reward Learning
- Robust Quadrupedal Locomotion on Sloped Terrains: A Linear Policy Approach
- SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning
- STReSSD: Sim-To-Real from Sound for Stochastic Dynamics
- Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs
- Safe Policy Learning for Continuous Control
- Sampling-based Reachability Analysis: A Random Set Theory Approach with Adversarial Sampling
- SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation
- The EMPATHIC Framework for Task Learning from Implicit Human Feedback
- The Emergence of Adversarial Communication in Multi-Agent Reinforcement Learning
- Time-Bounded Mission Planning in Time-Varying Domains with Semi-MDPs and Gaussian Processes
- Uncertainty-Aware Constraint Learning for Adaptive Safe Motion Planning from Demonstrations
- Visual Localization and Mapping with Hybrid SFA