Training neural network potentials

Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"

Parameter inference with SBI for TVB models.

Some methods for comparing network representations in deep learning and neuroscience.

Papers from the intersection of deep learning and neuroscience

A curated collection of resources and research related to the geometry of representations in the brain, deep networks, and beyond

Code to accompany the textbook "Modeling Neural Circuits Made Simple"

Reference sparse coding implementations for efficient learning and inference.

SHTOOLS - Spherical Harmonic Tools

Boltzmann Generators and Normalizing Flows in PyTorch

Wave propagation modules for PyTorch.

Connectivity algorithms that leverage the MNE-Python API.

Companion webpage to the book "Mathematics For Machine Learning"