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.

Python library to compute different properties of tight binding models

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

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.

paper lists and information on mean-field theory of deep learning

Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"

Implementation of deep implicit attention in PyTorch

Hartree-Fock-Bogoliubov solver for a generic interacting fermion Hamiltonian

Computational statistical mechanics of field-responsive polymer chains

Package for solving generalized BdG mean field theory of interacting systems.

Automatic Differentiation Mean Field Approach

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

Mean field theory and cavity method implementation.

description coming soon

A project to study Hartree-Fock technique in 1-D

A C++ program for solving the mean field equation in Holstein model and periodic Anderson model with Holstein phonons, with phonon displacement as the order parameter.

A collection of programs and scripts to solve and analyze the Kane-Mele-Hubbard model in a variety of (dynamical) mean-field settings

Implementation of Variational Mean Field Inference for dense Conditional Random Fields.

Numerical integration of mean-field equations for large-scale leaky integrate-and-fire neuronal network simulations incorporating synaptic plasticity via Graupner Brunel model. Includes support for a memory-induction stim-pop.