A project to study Hartree-Fock technique in 1-D
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Updated
Nov 3, 2017 - C++
A project to study Hartree-Fock technique in 1-D
Mean field theory and cavity method implementation.
Hartree Fock corrections to nearly free electron Bloch bands
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.
Path integral based Auxiliary field Monte-Carlo results for Fermionic Hubbard model using HF decoupling
description coming soon
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 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.
Automatic Differentiation Mean Field Approach
Hartree-Fock-Bogoliubov solver for a generic interacting fermion Hamiltonian
3 states magnetic model
Implementation of deep implicit attention in PyTorch
Package to perform tight binding calculation in tight binding models, with a friendly user interface
Projects of the Statistical Learning Theory class at ETH Zurich
Python library to compute different properties of tight binding models
Factorized variational approximation using a univariate Gaussian distribution over a single variable x.
Coordinate ascent mean-field variational inference (CAVI) using the evidence lower bound (ELBO) to iteratively perform the optimal variational factor distribution parameter updates for clustering.
Model Reduction of the Approximate Master Equation for Epidemic Processes on Complex Networks
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