We study the denoising of piecewise smooth graph signals that exhibit
in...
We present a neural-network-based architecture for 3D point cloud denois...
In this paper, we extend the sampling theory on graphs by constructing a...
As a collection of 3D points sampled from surfaces of objects, a 3D poin...
In this paper, we introduce a generalized value iteration network (GVIN)...
We present a new smooth, Gaussian-like kernel that allows the kernel den...
We present a framework for representing and modeling data on graphs. Bas...
We introduce a new supervised algorithm for image classification with
re...
In this paper we present a novel method for robust hyperspectral image
c...
We present a supervised hyperspectral image segmentation algorithm based...
We study signal recovery on graphs based on two sampling strategies: ran...
Classifiers with rejection are essential in real-world applications wher...
We consider the problem of signal recovery on graphs as graphs model dat...
In this paper we provide rigorous proof for the convergence of an iterat...