Scikit-network: Graph Analysis in Python
Not on the map. Why?
Abstract (arXiv)
Scikit-network is a Python package inspired by scikit-learn for the analysis of large graphs. Graphs are represented by their adjacency matrix in the sparse CSR format of SciPy. The package provides state-of-the-art algorithms for ranking, clustering, classifying, embedding and visualizing the nodes of a graph. High performance is achieved through a mix of fast matrix-vector products (using SciPy), compiled code (using Cython) and parallel processing. The package is distributed under the BSD license, with dependencies limited to NumPy and SciPy. It is compatible with Python 3.6 and newer. Source code, documentation and installation instructions are available online.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Sep 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 1; 2023: 2; 2024: 1; 2025: 0; 2026: 3.
8 papers.
- 2023Explanations of Black-Box Models based on Directional Feature Interactionscited by 15
- 2022Data-Driven Network Neuroscience: On Data Collection and Benchmarkcited by 12
- 2021Partition and Code: learning how to compress graphscited by 10
- 2026GABench: A Comprehensive Benchmark for Evaluating LLM Agents on Graph Analysis Taskscited by 2
- 2026Incorporating Deep Learning Design in Database Queriescited by 1
- 2023Improving Knowledge Distillation with Teacher's Explanationcited by 0
- 2024PlasmoData.jl -- A Julia Framework for Modeling and Analyzing Complex Data as Graphscited by 0
- 2026Neuro-Relational Programs: Unifying Queries and Neural Computation over Structured Datacited by 0
- 2026GABench: A Comprehensive Benchmark for Evaluating LLM Agents on Graph Analysis Tasks3 Aug 2026
- 2026Neuro-Relational Programs: Unifying Queries and Neural Computation over Structured Data10 Jun 2026
- 2026Incorporating Deep Learning Design in Database Queries22 May 2026
- 2024PlasmoData.jl -- A Julia Framework for Modeling and Analyzing Complex Data as Graphs21 Jan 2024
- 2023Improving Knowledge Distillation with Teacher's Explanation4 Oct 2023
- 2023Explanations of Black-Box Models based on Directional Feature Interactions16 Apr 2023
- 2022Data-Driven Network Neuroscience: On Data Collection and Benchmark11 Nov 2022
- 2021Partition and Code: learning how to compress graphs5 Jul 2021