no code implementations • 24 Jan 2024 • Ignacio Segovia-Dominguez, Yuzhou Chen, Cuneyt G. Akcora, Zhiwei Zhen, Murat Kantarcioglu, Yulia R. Gel, Baris Coskunuzer
This framework empowers the exploration of data by simultaneously varying multiple scale parameters.
no code implementations • 24 Jan 2024 • Baris Coskunuzer, Ignacio Segovia-Dominguez, Yuzhou Chen, Yulia R. Gel
In particular, we propose a new approach, named \textit{Temporal MultiPersistence} (TMP), which produces multidimensional topological fingerprints of the data by using the existing single parameter topological summaries.
1 code implementation • 18 May 2023 • Poupak Azad, Baris Coskunuzer, Murat Kantarcioglu, Cuneyt Gurcan Akcora
The rise of cryptocurrencies like Bitcoin, which enable transactions with a degree of pseudonymity, has led to a surge in various illicit activities, including ransomware payments and transactions on darknet markets.
1 code implementation • 24 Nov 2022 • Cuneyt Gurcan Akcora, Murat Kantarcioglu, Yulia R. Gel, Baris Coskunuzer
Second, we introduce a pruning algorithm for graphs to compute their persistence diagrams by removing the dominated vertices.
no code implementations • 7 Nov 2022 • Andac Demir, Baris Coskunuzer, Ignacio Segovia-Dominguez, Yuzhou Chen, Yulia Gel, Bulent Kiziltan
In computer-aided drug discovery (CADD), virtual screening (VS) is used for identifying the drug candidates that are most likely to bind to a molecular target in a large library of compounds.
1 code implementation • NeurIPS 2021 • Yuzhou Chen, Baris Coskunuzer, Yulia R. Gel
As a result, the new framework enables us to harness both the conventional information on the graph structure and information on the graph higher order topological properties.
no code implementations • ICLR 2022 • Yuzhou Chen, Ignacio Segovia-Dominguez, Baris Coskunuzer, Yulia Gel
Graph Neural Networks (GNNs) are proven to be a powerful machinery for learning complex dependencies in multivariate spatio-temporal processes.
1 code implementation • 10 Apr 2021 • Baris Coskunuzer, Cuneyt Gurcan Akcora, Ignacio Segovia Dominguez, Zhiwei Zhen, Murat Kantarcioglu, Yulia R. Gel
We derive theoretical guarantees on the stability of the new saw and multi-persistence grid functions and illustrate their applicability for graph classification tasks.
no code implementations • 11 Mar 2021 • Henry Adams, Baris Coskunuzer
We introduce several geometric notions, including the width of a homology class, to the theory of persistent homology.
Algebraic Topology Computational Geometry Geometric Topology 55N31, 55U10, 57R19, 62R40