7 citations · 20 across the 9 of their papers we have counts for
10 papers
Vectorization of Persistence Diagrams for Topological Data Analysis in R and Python Using TDAvec Package
Aleksei Luchinsky, Umar Islambekov
Persistent homology is a widely-used tool in topological data analysis (TDA) for understanding the underlying shape of complex data. By constructing a filtration of simplicial comp…
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…
Vector Summaries of Persistence Diagrams for Permutation-based Hypothesis Testing
Umar Islambekov, Hasani Pathirana
Over the past decade, the techniques of topological data analysis (TDA) have grown into prominence to describe the shape of data. In recent years, there has been increasing interes…
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…
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…
Lieb-Robinson Bounds for the Toda Lattice
Umar Islambekov, Robert Sims, Gerald Teschl
We establish locality estimates, known as Lieb-Robinson bounds, for the Toda lattice. In contrast to harmonic models, the Lieb-Robinson velocity for these systems do depend on the…