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Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey
Efficient and Stable Online Learning for Developmental Robots
Towards mastery of complex visuo-motor transformations
Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey
Towards mastery of complex visuo-motor transformations
Towards Autonomous Lunar Resource Excavation via Deep Reinforcement Learning
Uncertainty-Aware Attention Guided Sensor Fusion For Monocular Visual Inertial Odometry
V-MIN: efficient reinforcement learning through demonstrations and relaxed reward demands
On Generalizably Improving RANS Predictions of Flow Separation and Reattachment
Controlled Gaussian Process Dynamical Models with Application to Robotic Cloth Manipulation
Posenbasierte Intentionserkennung von ungeschützten Verkehrsteilnehmern aus einem Fahrzeug
Aerodynamics Analysis Tools for Flying Robots: Automated Tuft Recognition using Deep Learning
A maturity model for the autonomy of manufacturing systems
Progressive Bayesian Neural Networks
DOT: Dynamic Object Tracking for Visual SLAM
Distributed resource allocation in wireless networks.
ein spieltheoretisch lernendes Systemkonzept
Generalization of optimal motion trajectories for a biped walking machine based on machine learning
A Recursive Multi-step Machine Learning Approach for Airport Configuration Prediction
Schwingkomfortbewertung in Straßenbahnen mittels Maschinellen Lernens; 1. Auflage
Predicting Arrival and Departure Runway Assignments with Machine Learning
Creating a Culture of Continuous Learning: Solutions for Patient Safety
Input Image Adaption for Robust Direct SLAM using Deep Learning
Comparing Deep Neural Network Architectures using Transfer-Learning to Predict Cognitive States
Traffic Safety at German Roundabouts—A Replication Study
Real World Applications of AI/ML in Optimizing Airspace Operations
Learning Defects from Aircraft NDT data (Masterarbeit)
Recent efforts in Machine Learning for RANS modelling of separated flows
Predicting Cognitive States Using Machine Learning Fusion Paradigms to Reduce Model Uncertainty
Learning from All Operations – Expanding the Field of Vision to Improve Aviation Safety
Robot learning of container-emptying skills through haptic demonstration
Quantitative methods for the characterization of separated and intermittent multiphase flow patterns
Artificial Intelligence Enhancements to Imagery for Space Operations
1d-Convolutional Neural Network Architecture for Generalized Time-Segmentation Tasks
Collision Avoidance Approach Using Deep Reinforcement Learning
A Data-Driven Approach to Recognizing and Understanding Human Contributions to Aviation Safety
Rho-learning: a robotics oriented reinforcement learning algorithm