CyNetDiff -- A Python Library for Accelerated Implementation of Network Diffusion Models
In recent years, there has been increasing interest in network diffusion models and related problems. The most popular of these are the independent cascade and linear threshold models. Much of the recent experimental work done on these models requires a large number of simulations conducted on large graphs, a computationally expensive task suited for low-level languages. However, many researchers prefer the use of higher-level languages (such as Python) for their flexibility and shorter development times. Moreover, in many research tasks, these simulations are the most computationally intensive task, so it would be desirable to have a library for these with an interface to a high-level language with the performance of a low-level language. To fill this niche, we introduce CyNetDiff, a Python library with components written in Cython to provide improved performance for these computationally intensive diffusion tasks.
Code (1)
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
A TensorFlow implementation of Local Binary Patterns Transform
Feature extraction layers like Local Binary Patterns (LBP) transform can be very useful for improving the accuracy of machine learning and deep learning models depending on the problem type. Direct implementations of suc…
CPUGPUA Pressure-Based Diffusion Model for Influence Maximization on Social Networks
In many real-world scenarios, an individual's local social network carries significant influence over the opinions they form and subsequently propagate. In this paper, we propose a novel diffusion model -- the Pressure T…
py-irt: A Scalable Item Response Theory Library for Python
py-irt is a Python library for fitting Bayesian Item Response Theory (IRT) models. py-irt estimates latent traits of subjects and items, making it appropriate for use in IRT tasks as well as ideal-point models. py-irt is…
GPUCryo-RALib -- a modular library for accelerating alignment in cryo-EM
Thanks to automated cryo-EM and GPU-accelerated processing, single-particle cryo-EM has become a rapid structure determination method that permits capture of dynamical structures of molecules in solution, which has been …
BenchmarkingGPUISACDESlib: A Dynamic ensemble selection library in Python
DESlib is an open-source python library providing the implementation of several dynamic selection techniques. The library is divided into three modules: (i) \emph{dcs}, containing the implementation of dynamic classifier…