Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

Examples of parameter estimation in cardiac cell electrophysiology using Myokit and PINTS.

Simula Cardiac ElectroMechanics Solver

Pedagogical materials for learning COVID-19 transmission dynamics modelling

Simple Graph Data Extractor (used to be part of Myokit)

"Probabilistic Machine Learning" - a book series by Kevin Murphy

Home for our ontology definitions

A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.

Code for a dynamic multilevel Bayesian model to predict US presidential elections. Written in R and Stan.

Exploratory analysis of Bayesian models with Python

Bayesian Data Analysis course at Aalto

Data and code for reproducing the results in the nonlinear time-dependent leak paper.

Visualizations of the connections between chaos theory and fractals through the logistic map; made for Veritasium YouTube video

Code to add a mathematical model of voltage-clamp artefacts to your ion channel simulations

Figures and code for examples in WIREs review on calibrating electrophysiology models

Course materials for Research Software Engineering course.

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Code for the tutorials in the Fickle Heart model calibration with discrepancy 2020 paper.

Collection of experimental protocols in common patch clamp formats for rapid characterisation of ion channels

Rapid characterisation of hERG channel kinetics

Probabilistic Inference on Noisy Time Series