Abstract: Kernel-based reconstruction of graph signals was extensively studied in graph signal processing domain, which has been which has been verified to be efficient for real-world applications.

Abstract: 3D object detection is vital for many robotics applications. For tasks where a 2D perspective range image exists, we propose to learn a 3D representation directly from this range image view.

The problem consists in classifying molecular graphs into two categories, depending on whether or not they exhibit a specific function. To tackle this, we aim to explore graph kernels for generating ...