GitHub topics: markovian-epidemic-processes
wcota/dynSIS
Implementation of SIS epidemic model for large and heterogeneous networks using Fortran.
Language: Fortran - Size: 1.51 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 9 - Forks: 2
wcota/dynSIS-networkx
Networkx implementation of the SIS epidemic model for large and heterogeneous networks
Language: Python - Size: 28.3 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 14 - Forks: 4
wcota/dynSIS-py
Implementation of SIS epidemic model for large and heterogeneous networks
Language: Python - Size: 32.2 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 4
wcota/dynSIS-GA
Implementation of SIS epidemic model with a Gillespie Algorithm - NOT optimized
Language: Fortran - Size: 28.3 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 1
akshaykhadse/reinforcement-learning
Implementations of basic concepts dealt under the Reinforcement Learning umbrella. This project is collection of assignments in CS747: Foundations of Intelligent and Learning Agents (Autumn 2017) at IIT Bombay
Language: Python - Size: 20.4 MB - Last synced at: about 2 years ago - Pushed at: almost 7 years ago - Stars: 15 - Forks: 6
Ethan-CS/Equations
Program to find number of differential equations needed to express an SIR(P) network exactly.
Language: Java - Size: 524 KB - Last synced at: almost 2 years ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0
danielhanchen/Markovian_SIR_Deaths_Model
I noticed that traditional methods to predict a disease outbreak was by performing sentiment analysis on Twitter posts and Google Search terms. Unfortunately, these methods were inadequate, as Twitter and Google is not popular in all countries. So, I created a system to model and predict outbreaks without the need for social media. The system was able to update the probabilities of a virus from spreading from A to B in real time, and I plan to release it to the public next year. I also used Machine Learning and Deep Learning to predict larger long-term virus trends with Google Trends, and this acted as a validator for the MSIRD model.
Language: Jupyter Notebook - Size: 31 MB - Last synced at: 24 days ago - Pushed at: over 7 years ago - Stars: 3 - Forks: 2
