Machine learning algorithms for many-body quantum systems

Code for 'Solving Statistical Mechanics using Variational Autoregressive Networks'.

DeepErwin is a python 3.8+ package that implements and optimizes JAX 2.x wave function models for numerical solutions to the multi-electron Schrödinger equation. DeepErwin supports weight-sharing when optimizing wave functions for multiple nuclear geometries and the usage of pre-trained neural network weights to accelerate optimization.

A framework based on Tensorflow for running variational Monte-Carlo simulations of quantum many-body systems.

Infinite order automatic differentiation for Monte Carlo with unnormalized probability distribution

Code for 'From Tensor Network Quantum States to Tensorial Recurrent Neural Networks'.

Introduction to quantum Monte Carlo. From the foundations to state-of-the-art Restricted Boltzmann Machine ansatz.

Example class structure for use in FYS4411: Quantum mechanical systems at UiO.

Variational Quantum Monte Carlo for a molecule, using Fokker-Planck/Langevin approach

Code for 'Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks'.

Quantum Variational Monte Carlo with Neural Networks - Project repository for my master's thesis in computational physics at the University of Oslo

Neural Network Quantum State

Header only library for neural network quantum states

Advanced Data Assimilation Algorithms and Methods

Supporting code for "Systematic improvement of neural network quantum states using Lanczos (NeurIPS 2022)""

📝 Code for the paper "Many-body quantum sign structures as non-glassy Ising models"

Group work for Solid State physics course at Aalto University