Search Results for author:
Found 5 papers, 1 papers with code
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain
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 Learning and Generative Modeling (GRaM).
ICML 2023 Topological Deep Learning Challenge : Design and Results
This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning.
Topological Signal Processing using the Weighted Ordinal Partition Network
For this task, we turn to the field of topological data analysis (TDA), which encodes information about the shape and structure of data.
Effects of Correlated Noise on the Performance of Persistence Based Dynamic State Detection Methods
The ability to characterize the state of dynamic systems has been a pertinent task in the time series analysis community.
Persistent Homology of Complex Networks for Dynamic State Detection
Specifically, we show how persistent homology, a tool from TDA, can be used to yield a compressed, multi-scale representation of the graph that can distinguish between dynamic states such as periodic and chaotic behavior.
Chaotic Dynamics Computational Geometry Information Theory Information Theory Data Analysis, Statistics and Probability
