Search Results for author: Hans Riess

Found 7 papers, 0 papers with code

Path Signatures and Graph Neural Networks for Slow Earthquake Analysis: Better Together?

no code implementations5 Feb 2024 Hans Riess, Manolis Veveakis, Michael M. Zavlanos

The path signature, having enjoyed recent success in the machine learning community, is a theoretically-driven method for engineering features from irregular paths.

Earthquake prediction

Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and Back

no code implementations20 Mar 2023 Claudio Battiloro, Zhiyang Wang, Hans Riess, Paolo Di Lorenzo, Alejandro Ribeiro

We define tangent bundle filters and tangent bundle neural networks (TNNs) based on this convolution operation, which are novel continuous architectures operating on tangent bundle signals, i. e. vector fields over the manifolds.

Stable and Transferable Hyper-Graph Neural Networks

no code implementations11 Nov 2022 Mikhail Hayhoe, Hans Riess, Victor M. Preciado, Alejandro Ribeiro

To do so, we provide a framework for bounding the stability and transferability error of GNNs across arbitrary graphs via spectral similarity.

Tangent Bundle Filters and Neural Networks: from Manifolds to Cellular Sheaves and Back

no code implementations26 Oct 2022 Claudio Battiloro, Zhiyang Wang, Hans Riess, Paolo Di Lorenzo, Alejandro Ribeiro

In this work we introduce a convolution operation over the tangent bundle of Riemannian manifolds exploiting the Connection Laplacian operator.

Denoising

Quiver Signal Processing (QSP)

no code implementations22 Oct 2020 Alejandro Parada-Mayorga, Hans Riess, Alejandro Ribeiro, Robert Ghrist

In this paper we state the basics for a signal processing framework on quiver representations.

A Temporal Logic-Based Hierarchical Network Connectivity Controller

no code implementations1 Sep 2020 Hans Riess, Yiannis Kantaros, George Pappas, Robert Ghrist

We show that these constraints along with the requirement of propagating information in the network can be captured by a Linear Temporal Logic (LTL) framework.

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