Machine learning algorithms for many-body quantum systems

UFL - Unified Form Language

Next generation FEniCS Form Compiler for finite element forms

This is a 'hands-on' tutorial for the RIKEN International School on Data Assimilation (RISDA2018).

A Python implementation of Monge optimal transportation

Projected time-dependent Variational Monte Carlo (p-tVMC) method based on infidelity optimization for variational simulation of quantum dynamics.

This is a complete python package that explores variational methods for 2D image segmentation popularly known as snakes. The package consists of already implemented methods like Chan Vese & Yezzi (mean seperation), Bhattacharya (Probability distribution separation), also, Interactive feedback control approach to snakes

Official PyTorch code for UAI 2024 paper "ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-variable Context Encoding"

Code for A Weighted Mini-Bucket Bound for Solving Influence Diagrams (UAI 2019) and Join-Graph Decomposition Bounds for Influence Diagrams (UAI 2018).

Gutzwiller variational approach for the Bose-Hubbard model, with simulated-annealing optimization

Implementation of the Variational Method for Quantum Mechanics in python.

Weather routing via variational methods

FlowBasis: Variational solutions of perturbed quantum harmonic oscillator problems via augmented basis sets.

👀🛡️ Code for the paper “Blending adversarial training and representation-conditional purification via aggregation improves adversarial robustness” by Emanuele Ballarin, Alessio Ansuini and Luca Bortolussi (2025)

variPEPS -- Versatile tensor network library for variational ground state simulations in two spatial dimensions

A GUI for the Variational_Principle repository in PyQT

Python scripts for trying various data assimilation algorithms with simple toy models

Implementation of neural coherent states, arXiv:2105.15193

Variationally enhanced sampling for single-particle langevin dynamics with neural network bias potentials and path collective variables. Based on OpenMM + PyTorch.