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This repository contains the Python code used in the publication 'Bayesian decomposition of the Galactic multi-frequency sky using probabilistic autoencoders' by Milosevic et al., 2020.

Example of machine learning for Hirshfeld ratios.

Attached to book chapter in Handbook of Materials Modeling

This is a fork of the ALCHEMIC astrochemical modelling code (Semenov et al. 2010). The code is adapted to model the chemical evolution of SPH trajectories from hydrodynamic molecular cloud simulations, using complex chemical networks.

Interspecific collaboration: stereo calibration and 3D Habitat reconstruction/Tracking

CG Surface Hopping - simulation and analysis scripts

Connectomic Data Analysis Toolkit

Jupyter notebooks