Many real-world decision-making tasks, such as safety-critical scenarios...
Deploying Deep Neural Networks (DNNs) on tiny devices is a common trend ...
Training DRL agents is often a time-consuming process as a large number ...
VQA have attracted a lot of attention from the quantum computing communi...
Beamforming-capable antenna arrays overcome the high free-space path los...
Humans innately measure distance between instances in an unlabeled datas...
Reinforcement learning (RL) has shown to reach super human-level perform...
Large Deep Neural Networks (DNNs) are the backbone of today's artificial...
The data representation in a machine-learning model strongly influences ...
Recent localization frameworks exploit spatial information of complex ch...
Autonomous driving has the potential to revolutionize mobility and is he...
Many scenarios in mobility and traffic involve multiple different agents...
The correct interpretation and understanding of deep learning models is
...
Common representation learning (CRL) learns a shared embedding between t...
Handwriting is one of the most frequently occurring patterns in everyday...
Deep Reinforcement Learning (RL) has considerably advanced over the past...
Active learning (AL) prioritizes the labeling of the most informative da...
This paper presents a novel motion and trajectory planning algorithm for...
Visual Odometry (VO) accumulates a positional drift in long-term robot
n...