[ECML-PKDD2022] EpiGNN: Exploring Spatial Transmission with Graph Neural Network for Regional Epidemic Forecasting

The "Analysis of Information Networks" repository contains six exercises that explore key concepts in network analysis. From random network generation to link prediction and recommender systems, each exercise provides hands-on experience with metrics, visualizations, and real-world applications.

Spatial MultiAgent RL for Epidemic Control with Heterogeneous Risk Preferences

A bi-virus epidemic model for networks with duty-cycled wireless sensors

Epidemic spread simulation using cellular automata with intervention strategies and real-time visualisation in Python.

Notebooks used or made in development of prediksicovidjatim

A numerical simulation of the SVEIR epidemic model (Susceptible-Vaccinated-Exposed-Infected-Recovered) incorporating spatial diffusion. Solves the system of differential equations to analyze influenza spread and vaccination impact.

An uncertainty-driven probabilistic framework for modeling worm propagation in large-scale networks. It uses stochastic infection rates to capture bursty behavior, adaptive slowdowns, and defense mechanisms, improving prediction accuracy over traditional models while remaining safe, reproducible, and suitable for cybersecurity research.

Teaching-oriented ODE epidemic mini-lab with SI, SIR, and SEIR models, parameter sweeps, and interpretable metrics.