03-16 Autonomous Driving | ActiveAD: Planning-Oriented Active Learning for End-to-End Autonomous Driving
02-29 Autonomous Driving | VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning
02-28 Reinforcement Learning | Planning with Diffusion for Flexible Behavior Synthesis (berkeley&mit)
02-01 Imitation Learning | Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation (Stanford University)
01-31 Autonomous Driving | OK-Robot: What Really Matters in Integrating Open-Knowledge Models for Robotics
01-24 Autonomous Driving | End-To-End Planning of Autonomous Driving in Industry and Academia: 2022-2023
01-22 Autonomous Driving | Recent Advancements in End-to-End Autonomous Driving using Deep Learning: A Survey
01-11 Autonomous Driving | Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving
09-14 Autonomous Driving | M2I: From Factored Marginal Trajectory Prediction to Interactive Prediction
05-09 Autonomous Driving | MTR-A: 1st Place Solution for 2022 Waymo Open Dataset Challenge - Motion Prediction
05-05 Autonomous Driving | Motion Transformer with Global Intention Localization and Local Movement Refinement
04-01 Autonomous Driving | Multipath++: Efficient information fusion and trajectory aggregation for behacior prediction
10-14 Autonomous Driving | Path Planning for Autonomous Vehicles in Unknown Semi-structured Environments
09-30 Autonomous Driving | From smart parking towards autonomous valet parking: A survey, challenges and future Works
09-30 Autonomous Driving | Parallel, Angular and Perpendicular Parking for Self-Driving Cars using Deep Reinforcement Learning
09-28 Autonomous Driving | DL-IAPS and PJSO: A Path/Speed Decoupled Trajectory Optimization and its Application in Autonomous Driving (Baidu, 2020)
09-20 Autonomous Driving | BEVFormer: Learning Bird’s-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers
08-24 Autonomous Driving | On the Choice of Data for Efficient Training and Validation of End-to-End Driving Models
08-17 Autonomous Driving | SMARTS Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving (Huawei)
08-04 Autonomous Driving | UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning
08-03 Autonomous Driving | Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients
07-22 Autonomous Driving | MotionCNN: A Strong Baseline for Motion Prediction in Autonomous Driving (2022)
07-16 Autonomous Driving | ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst (Waymo, 2018)
07-14 Autonomous Driving | Exploring Imitation Learning for Autonomous Driving with Feedback Synthesizer and Differentiable Rasterization (2021, Apollo 6.0)
09-06 Neuroscience | Integration of Reinforcement Learning and Optimal Decision-Making Theories of the Basal Ganglia
07-22 Reinforcement Learning | Intrinsically Motivated Reinforcement Learning: An Evolutionary Perspective
07-14 Reinforcement Learning | Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation
07-06 Reinforcement Learning | Option Discovery in Hierarchical Reinforcement Learning using Spatio-Temporal Clustering
07-01 Reinforcement Learning | Hierarchical Deep Reinforcement Learning for Continuous Action Control
03-31 Neuroscience | Adaptation to Visuomotor Rotation Through Interaction Between Posterior Parietal and Motor Cortical Areas
03-31 Neuroscience | The posterior parietal cortex Sensorimotor interface for the planning and online control of visually guided movements
03-30 Reinforcement Learning | Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics a Survey
03-29 Memristor‐Based Biologically Plausible Memory Based on Discrete and Continuous Attractor Networks for Neuromorphic Systems
03-28 Neuroscience | Neuronal Correlates of Motor Performance and Motor Learning in the Primary Motor Cortex of Monkeys Adapting to an External Force Field
03-26 Neuroscience | Motor Memory Is Encoded as a Gain-Field Combination of Intrinsic and Extrinsic Action Representations
03-25 Neuroscience | A Gain-Field Encoding of Limb Position and Velocity in the Internal Model of Arm Dynamics
09-26 Neuroscience | A subcortical excitatory circuit for sensory-triggered predatory hunting in mice
09-16 Reinforcement Learning | Making Efficient Use of Demonstrations to Solve Hard Exploration Problems (R2D3)