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Found 11 papers, 1 papers with code
PosDiffNet: Positional Neural Diffusion for Point Cloud Registration in a Large Field of View with Perturbations
We leverage a graph neural partial differential equation (PDE) based on Beltrami flow to obtain high-dimensional features and position embeddings for point clouds.
DistilVPR: Cross-Modal Knowledge Distillation for Visual Place Recognition
The utilization of multi-modal sensor data in visual place recognition (VPR) has demonstrated enhanced performance compared to single-modal counterparts.
Modeling Sparse Graph Sequences and Signals Using Generalized Graphons
Our signal processing framework provides a comprehensive approach to analyzing and processing signals on graph sequences, even if they are sparse.
A sampling construction of graphon 1-norm convergence
The note also contains errata of the previous version of the note.
Spectral Convergence of Simplicial Complex Signals
We recall the notion of a complexon as the limit of a simplicial complex sequence [1].
Generalized Graphon Process: Convergence of Graph Frequencies in Stretched Cut Distance
This random graph process converges to the generalized graphon in stretched cut distance.
Kernel Based Reconstruction for Generalized Graph Signal Processing
In this paper, we study GGSP signal reconstruction as a kernel ridge regression (KRR) problem.
Generalized signals on simplicial complexes
Topological signal processing (TSP) over simplicial complexes typically assumes observations associated with the simplicial complexes are real scalars.
Graph signal processing with categorical perspective
In this paper, we propose a framework for graph signal processing using category theory.
On distributional graph signals
We develop signal processing tools to study the new notion of distributional graph signals.
Wide-Sense Stationarity in Generalized Graph Signal Processing
We consider statistical graph signal processing (GSP) in a generalized framework where each vertex of a graph is associated with an element from a Hilbert space.
