Abstract: In view of the problems of the current professional introduction course, such as wide scope of knowledge, lack of in-depth knowledge explanation and weak relevance of each course content, ...
Abstract: Graph convolutional neural networks (GCNN) have been widely used in graph learning and related applications. It has been identified that the filters in the state-of-the-art spectral graph ...
This course aims to develop a computational view of stochastic differential equations (SDEs) for students who have an applied or engineering background, e.g., machine learning, signal processing, ...
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