This material outlines a hands-on workshop on learning how to develop AI-based autonomous mobile robot for university students and engineers of all skill levels. MATLAB and Simulink are utilized as an ...
Abstract: We report a newly developed room-temperature (RT) shimming method for high-temperature superconducting (HTS) magnets employing a deep Q-network (DQN), a type of reinforcement learning theory ...
Abstract: Deep learning techniques are empowering many space based applications with good speed and accuracy. The application includes categorizing astronomical data, identifying celestial bodies, ...
1 College of Engineering and Computing, Florida International University, Miami, USA. 2 School of Economics, Capital University of Economics and Business, Beijing, China. 3 School of Information ...
Yoshua Bengio, Yann LeCun, and Geoffrey Hinton are recipients of the 2018 ACM A.M. Turing Award for breakthroughs that have made deep neural networks a critical component of computing. Research on ...
We consider the question of 30-min prediction of blood glucose levels measured by continuous glucose monitoring devices, using clinical data. While most studies of this nature deal with one patient at ...
Wesfeiler-Lehman Neural Machine (WLNM) is a subgraph-based link prediction method leveraging deep learning to automatically learn graph structure features for link prediction from links' enclosing ...
Neural systems include interactions that occur across many scales. Two divergent methods for characterizing such interactions have drawn on the physical analysis of critical phenomena and the ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results