39 citations · 103 across the 8 of their papers we have counts for
8 papers
Topological Schrödinger Bridge Matching
Maosheng Yang
Given two boundary distributions, the Schrödinger Bridge (SB) problem seeks the ``most likely`` random evolution between them with respect to a reference process. It has revealed r…
Hodge-Compositional Edge Gaussian Processes
Maosheng Yang, Viacheslav Borovitskiy, Elvin Isufi
We propose principled Gaussian processes (GPs) for modeling functions defined over the edge set of a simplicial 2-complex, a structure similar to a graph in which edges may form tr…
Convolutional Learning on Simplicial Complexes
Maosheng Yang, Elvin Isufi
We propose a simplicial complex convolutional neural network (SCCNN) to learn data representations on simplicial complexes. It performs convolutions based on the multi-hop simplici…
Convolutional Filtering in Simplicial Complexes
Elvin Isufi, Maosheng Yang
This paper proposes convolutional filtering for data whose structure can be modeled by a simplicial complex (SC). SCs are mathematical tools that not only capture pairwise relation…
Simplicial Convolutional Filters
Maosheng Yang, Elvin Isufi, Michael T. Schaub +1
We study linear filters for processing signals supported on abstract topological spaces modeled as simplicial complexes, which may be interpreted as generalizations of graphs that…
Simplicial Convolutional Neural Networks
Maosheng Yang, Elvin Isufi, Geert Leus
Graphs can model networked data by representing them as nodes and their pairwise relationships as edges. Recently, signal processing and neural networks have been extended to proce…
Finite Impulse Response Filters for Simplicial Complexes
Maosheng Yang, Elvin Isufi, Michael T. Schaub +1
In this paper, we study linear filters to process signals defined on simplicial complexes, i.e., signals defined on nodes, edges, triangles, etc. of a simplicial complex, thereby g…
Node-Adaptive Regularization for Graph Signal Reconstruction
Maosheng Yang, Mario Coutino, Geert Leus +1
A critical task in graph signal processing is to estimate the true signal from noisy observations over a subset of nodes, also known as the reconstruction problem. In this paper, w…