Machine learning algorithms for many-body quantum systems
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Updated
Jul 11, 2025 - Python
Machine learning algorithms for many-body quantum systems
Next generation FEniCS Form Compiler for finite element forms
UFL - Unified Form Language
A Python implementation of Monge optimal transportation
This is a 'hands-on' tutorial for the RIKEN International School on Data Assimilation (RISDA2018).
Projected time-dependent Variational Monte Carlo (p-tVMC) method based on infidelity optimization for variational simulation of quantum dynamics.
variPEPS -- Versatile tensor network library for variational ground state simulations in two spatial dimensions
A Python interface to parallel data assimilation framework - pyPDAF
Gutzwiller variational approach for the Bose-Hubbard model, with simulated-annealing optimization
FlowBasis: Variational solutions of perturbed quantum harmonic oscillator problems via augmented basis sets.
Official PyTorch code for UAI 2024 paper "ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-variable Context Encoding"
Implementation of the Variational Method for Quantum Mechanics in python.
👀🛡️ Code for the paper “Carefully Blending Adversarial Training and Purification Improves Adversarial Robustness” by Emanuele Ballarin, Alessio Ansuini and Luca Bortolussi (2024)
Weather routing via variational methods
Python scripts for trying various data assimilation algorithms with simple toy models
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
Variationally enhanced sampling for single-particle langevin dynamics with neural network bias potentials and path collective variables. Based on OpenMM + PyTorch.
Code for A Weighted Mini-Bucket Bound for Solving Influence Diagrams (UAI 2019) and Join-Graph Decomposition Bounds for Influence Diagrams (UAI 2018).
A GUI for the Variational_Principle repository in PyQT
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