Antonio-Cruciani

TBC

percolationApproximation

Implementation of the approach described in the paper Estimating the Percolation Centrality of Large Networks through Pseudo-dimension Theory.

geocoding_google_map

Using the Google Maps API, this Python script streamlines geocoding addresses from an Excel file. It extracts latitude and longitude information and saves results in separate Excel files. Designed for GSSI members to pinpoint lunch coupon locations. A Google Maps map visualizes the data, with access limited to GSSI accounts.

CentRA

Efficient Centrality Maximization with Rademacher Averages (KDD 2023)

ProbGraphBetwn

pybind11

Seamless operability between C++11 and Python

MPSP-Centrality

ML-Course-Notes

🎓 Sharing machine learning course / lecture notes.

TENET.jl

A Julia temporal network library

TSBProxy

Repository associated to paper "Proxying betweenness in Temporal Networks: A comparative Analysis"

SILVAN

Repo for the SILVAN paper

GRETEL

Graph Counterfactual Explanation Evaluation Framework

BeautifulAlgorithms.jl

Concise and beautiful algorithms written in Julia

littleballoffur

Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)

infection

kadabra

KADABRA is an ADaptive Algorithm for Betweenness via Random Approximation

best-of-ml-python

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

cseq

RELEASES HERE -> https://github.com/omainv/cseq/releases

Higgs-Boson-Challange-2020-EPFL

A classification problem on a big physical dataset simulated by the ATLAS experiment from CERN - @ EPFL

HoneyChain-MMORPG-Blockchain-based-game-

An MMORPG Blockchain based game

tably

Python command-line script for converting .csv data to LaTeX tables

msr-vtt-it

A large scale dataset for Video Captioning in Italian

mscoco-it

A large scale dataset for Image Captioning in Italian

psds

Efficient Prefix-Sum data structures in C++.

MHSE

We propose two algorithms to efficiently estimate the effective diameter and other distance metrics on very large graphs that are based on the neighborhood function such as the exact diameter, the (effective) radius or the average distance.