Abstract: This paper presents a new, supervised, hierarchical clustering algorithm (SUHICLUST) for fuzzy model identification. The presented algorithm solves the problem of global model accuracy, ...

Abstract: As advances in the technologies of predicting protein interactions, huge data sets portrayed as networks have been available. Identification of functional modules from such networks is ...

2022 IEEE/ACM International Workshop on Hierarchical Parallelism for Exascale Computing (HiPar) We introduce a new high-performance design for parallelism within the Quantum Monte Carlo code QMCPACK.

The aim of this project is to aggregate, polish, and standardise the existing clustering benchmark batteries referred to across the machine learning and data mining literature, and to introduce new ...

Code for web scraping the OSRS hiscores, along with the resulting dataset. Code for a machine learning pipeline which clusters the player population by account similarity. An interactive web ...

Haplotype identification, characterization and visualization are important for large-scale analysis and use in population genomics. Many tools have been developed to visualize haplotypes, but it is ...

Here we developed an open-source Python-based library called Python rodent Analysis and Tracking (PyRAT). Our library analyzes tracking data to classify distinct behaviors, estimate traveled distance, ...