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pymc3

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano

pynm

Python implementation of Normative Modelling

pyprobml

Python code for "Machine learning: a probabilistic perspective" (2nd edition)

pyrates

Open-source, graph-based Python simulator and parameter analysis toolbox for dynamical systems (pre-implemented and custom models). Mainly designed for neural population models.

pysindy

A package for the sparse identification of nonlinear dynamical systems from data

pysmc

pystan

PyStan, the Python interface to Stan

pytorch-deep-learning

Deep Learning (with PyTorch)

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

pytorch-tutorial-1

rknn

sbi

Simulation-based inference toolkit

sbi-workshop

SBI Workshop jointly by Helmholtz AI + ML ⇌ Science Colaboratory

scikit-learn-mooc

scikit-learn-mooc

scikit-optimize

Sequential model-based optimization with a `scipy.optimize` interface

simple-brain-plot

brainPlot is a MATLAB function to create simple line-art brain plots.

singleneurondynamics

Single Neuron Dynamics

sourceestimation

SEEG Source Localization

spectral_connectivity

Frequency domain functional and directed connectivity analysis tools for electrophysiological data

spectralpowerfitting

Optimal Model Parameter Estimation From EEG Power Spectrum Features Observed During General Anesthesia, Hashemi et al, Neuroinformatics 2018

ssm

Bayesian learning and inference for state space models

sta-663-2018

stan

Stan development repository (home page is linked below). The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.

stan_pkpd_examples

stat_rethinking_2022

Statistical Rethinking course winter 2022

statistical-rethinking-with-python-and-pymc3

Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath

torchts

Time series forecasting with PyTorch

tutorial-sampling-enhanced-w-generative-models

tvb-tutorial

uvadlc_notebooks

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2022/Spring 2022