1 citations · 1 across the 8 of their papers we have counts for
10 papers
Graph Data Augmentation via Contrastive Generator Inversion ()
Mateusz Stolarski, Michał Czuba, Łukasz Kraiński +4
Graphs provide a natural representation of many complex systems, ranging from social platforms to ecosystems. However, the development of graph-based machine learning methods is of…
Going in Circles: Collaborative Multi-Robot Treasure Hunting
Bogumil Kaminski, Pawel Pralat, Maria Sadza
This paper investigates a multi-robot search-and-visit problem involving robots starting at the origin and unknown treasures hidden on the unit circle . The ro…
Twinning Complex Networked Systems: Data-Driven Calibration of the mABCD Synthetic Graph Generator
Piotr Bródka, Michał Czuba, Bogumił Kamiński +4
The increasing availability of relational data has contributed to a growing reliance on network-based representations of complex systems. Over time, these models have evolved to ca…
A Pragmatic Method for Comparing Clusterings with Overlaps and Outliers
Ryan DeWolfe, Paweł Prałat, François Théberge
Clustering algorithms are an essential part of the unsupervised data science ecosystem, and extrinsic evaluation of clustering algorithms requires a method for comparing the detect…
The Needle is a Thread: Finding Planted Paths in Noisy Process Trees
Maya Le, Paweł Prałat, Aaron Smith +1
Motivated by applications in cybersecurity such as finding meaningful sequences of malware-related events buried inside large amounts of computer log data, we introduce the "plante…
Achievable Burning Densities of Growing Grids
Jordan Barrett, Karen Gunderson, JD Nir +1
Graph burning is a discrete-time process on graphs where vertices are sequentially activated and burning vertices cause their neighbours to burn over time. In this work, we focus o…
The Artificial Benchmark for Community Detection with Outliers and Overlapping Communities (ABCD+)
Jordan Barrett, Ryan DeWolfe, Bogumił Kamiński +3
The Artificial Benchmark for Community Detection (ABCD) graph is a random graph model with community structure and power-law distribution for both degrees and community sizes. The…
Network Embedding Exploration Tool (NEExT)
Ashkan Dehghan, Paweł Prałat, François Théberge
Many real-world and artificial systems and processes can be represented as graphs. Some examples of such systems include social networks, financial transactions, supply chains, and…
Improving community detection via community association strength scores
Jordan Barrett, Ryan DeWolfe, Bogumił Kamiński +3
Community detection methods play a central role in understanding complex networks by revealing highly connected subsets of entities. However, most community detection algorithms ge…
Counting simplicial pairs in hypergraphs
Jordan Barrett, Paweł Prałat, Aaron Smith +1
We present two ways to measure the simplicial nature of a hypergraph: the simplicial ratio and the simplicial matrix. We show that the simplicial ratio captures the frequency, as w…