7 citations · 13 across the 4 of their papers we have counts for
5 papers
A computationally efficient framework for vector representation of persistence diagrams
Kit C. Chan, Umar Islambekov, Alexey Luchinsky +1
In Topological Data Analysis, a common way of quantifying the shape of data is to use a persistence diagram (PD). PDs are multisets of points in computed using tools…
Dissecting Ethereum Blockchain Analytics: What We Learn from Topology and Geometry of Ethereum Graph
Yitao Li, Umar Islambekov, Cuneyt Akcora +3
Blockchain technology and, in particular, blockchain-based cryptocurrencies offer us information that has never been seen before in the financial world. In contrast to fiat currenc…
Harnessing the power of Topological Data Analysis to detect change points in time series
Umar Islambekov, Monisha Yuvaraj, Yulia R. Gel
We introduce a novel geometry-oriented methodology, based on the emerging tools of topological data analysis, into the change point detection framework. The key rationale is that c…
Unsupervised Space-Time Clustering using Persistent Homology
Umar Islambekov, Yulia Gel
This paper presents a new clustering algorithm for space-time data based on the concepts of topological data analysis and in particular, persistent homology. Employing persistent h…
ChainNet: Learning on Blockchain Graphs with Topological Features
Nazmiye Ceren Abay, Cuneyt Gurcan Akcora, Yulia R. Gel +4
With emergence of blockchain technologies and the associated cryptocurrencies, such as Bitcoin, understanding network dynamics behind Blockchain graphs has become a rapidly evolvin…