6 papers
The Wigner-Ville Transform as an Information Theoretic Tool in Radio-frequency Signal Analysis
Erik Lentz, Emily Ellwein, Bill Kay +2
This paper presents novel interpretations to the field of classical signal processing of the Wigner-Ville transform as an information measurement tool. The transform's utility in d…
Entropic Analysis of Time Series through Kernel Density Estimation
Audun Myers, Bill Kay, Iliana Alvarez +5
This work presents a novel framework for time series analysis using entropic measures based on the kernel density estimate (KDE) of the time series' Takens' embeddings. Using this…
Talking to GDELT Through Knowledge Graphs
Audun Myers, Max Vargas, Sinan G. Aksoy +4
In this work we study various Retrieval Augmented Regeneration (RAG) approaches to gain an understanding of the strengths and weaknesses of each approach in a question-answering an…
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain
Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna +70
This paper describes the 2nd edition of the ICML Topological Deep Learning Challenge that was hosted within the ICML 2024 ELLIS Workshop on Geometry-grounded Representation Learnin…
Permutation Entropy for Signal Analysis
Bill Kay, Audun Myers, Thad Boydston +4
Shannon Entropy is the preeminent tool for measuring the level of uncertainty (and conversely, information content) in a random variable. In the field of communications, entropy ca…
Understanding High-Order Network Structure using Permissible Walks on Attributed Hypergraphs
Enzo Battistella, Sean English, Robert Green +6
Hypergraphs have been a recent focus of study in mathematical data science as a tool to understand complex networks with high-order connections. One question of particular relevanc…