activity
20232026
most citedA fast topological approach for predicting anomalies in time-varying graphs

1 citations · 4 across the 6 of their papers we have counts for

collaborators

5 papers

cs.CR20241 cited

Machine Learning for Blockchain Data Analysis: Progress and Opportunities

Poupak Azad, Cuneyt Gurcan Akcora, Arijit Khan

Blockchain technology has rapidly emerged to mainstream attention, while its publicly accessible, heterogeneous, massive-volume, and temporal data are reminiscent of the complex dy…

cs.LG20241 cited

EMP: Effective Multidimensional Persistence for Graph Representation Learning

Ignacio Segovia-Dominguez, Yuzhou Chen, Cuneyt G. Akcora +4

Topological data analysis (TDA) is gaining prominence across a wide spectrum of machine learning tasks that spans from manifold learning to graph classification. A pivotal techniqu…

cs.LG20241 cited

Explaining the Power of Topological Data Analysis in Graph Machine Learning

Funmilola Mary Taiwo, Umar Islambekov, Cuneyt Gurcan Akcora

Topological Data Analysis (TDA) has been praised by researchers for its ability to capture intricate shapes and structures within data. TDA is considered robust in handling noisy a…

cs.CR2023

Chainlet Orbits: Topological Address Embedding for the Bitcoin Blockchain

Poupak Azad, Baris Coskunuzer, Murat Kantarcioglu +1

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…

cs.LG20231 cited

A fast topological approach for predicting anomalies in time-varying graphs

Umar Islambekov, Hasani Pathirana, Omid Khormali +2

Large time-varying graphs are increasingly common in financial, social and biological settings. Feature extraction that efficiently encodes the complex structure of sparse, multi-l…