Michael Ajao-olarinoye (michaelajao)

michaelajao

Geek Repo

Company:coventry universiy

Location:coventry, united kingdom

Home Page:https://www.linkedin.com/in/michael-ajao/

Twitter:@michaelajao

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Michael Ajao-olarinoye's repositories

al-folio

A beautiful, simple, clean, and responsive Jekyll theme for academics

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databook_python

IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz

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EINNs

[AAAI-23] Epidemiologically-informed Neural Networks

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enhancing-forecast-COVID-19

Contains the scripts for the paper entitled "Enhancing the estimation of compartmental model parameters for COVID-19 data with a high level of uncertainty".

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EpiSciML-Tutorials

Julia for Epidemiology - With a Scientific Machine Learning Perspective

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EulerPINNs_for_covidODEs

Euler and deep learning approach to solve ordinary equations and estimate parameters.

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fall-in-love-with-julia

An introductory 101 series to get to know the power of Julialang

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harmonic-oscillator-pinn-workshop

Introductory workshop on PINNs using the harmonic oscillator

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KI2022-tutorial-universal-differential-equations

Universal Differential Equations in Julia - 3h Tutorial for KI2022

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modeling-examples

Gurobi modeling examples

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Modern-Time-Series-Forecasting-with-Python-2E

Modern Time Series Forecasting with Python 2E, Published by Packt

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PINNs4COVID19

This repository was built to house the experimental data and code from the paper.

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Prediction-COVID-19

Predicting the number of COVID-19 infections with DL like RNN, LSTM and PINN

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pyblish

Making publishing quality plots from python.

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PyTorchUltimateMaterial

This repo holds material for the Udemy course "PyTorch Ultimate"

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sir-julia

Various implementations of the classical SIR model in Julia

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vaccines-COVID-19

Code to replicate analysis and figures supporting the findings of the manuscript entitled "Impacts of a delayed and slow-paced vaccination on cases and deaths during the COVID-19 pandemic: a modelling study"

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