Easy whole-brain modeling for computational neuroscientists 🧠💻👩🏿‍🔬

Python library to compute properties of quantum tight binding models, including topological, electronic and magnetic properties and including the effect of many-body interactions.

Implementation of deep implicit attention in PyTorch

User-friendly open-source software to design and solve tight-binding models, addressing electronic properties, topology, interactions, non-collinear magnetism, and unconventional superconductivity, among others.

Package to perform tight binding calculation in tight binding models, with a friendly user interface

Physics-inspired transformer modules based on mean-field dynamics of vector-spin models in JAX

Python library to compute different properties of tight binding models

Automatic Differentiation Mean Field Approach

Mean field methods in the context of continuum mechanics with special focus on orientation averaging homogenization

This repository contains the code to reproduce the experiments performed in the Dynamical Mean-Field Theory of Self-Attention Neural Networks article.

Mean field theory and cavity method implementation.

Mean field variational Gaussian process algorithm. This repository contains a python3 implementation of the variational mean field algorithm as described in the paper: Physical Review E. vol. 91, 2015, 012148.

This repo provide numerical result of Caroli-de Gennes-Matricon(CdGM) mode and pair potential of an isolated quantum vortex in a two-dimensional superconductor .

Implementation of Mean Field Multi-Agent Reinforcement Learning (MF-MARL), featuring MF-Q and MF-AC algorithms for scalable learning in multi-agent environments like the Ising Model and Battle Game.

Dashboard documentation for the simulating the evolution of object proportions under a mean field approach.

Model Reduction of the Approximate Master Equation for Epidemic Processes on Complex Networks