Machine learning algorithms for many-body quantum systems
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Updated
Jun 9, 2024 - 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).
Interface to run Diva software tool (spatial interpolation).
Parallel Data Assimilation Framework
Variational Osmosis for Non-Linear Image Fusion
Projected time-dependent Variational Monte Carlo (p-tVMC) method based on infidelity optimization for variational simulation of quantum dynamics.
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.
Implementation of the Variational Method for Quantum Mechanics in python.
Advanced Data Assimilation Algorithms and Methods
A Python interface to parallel data assimilation framework - pyPDAF
Variational approximation by Gridap package to resolve T.I.S.E. in Julia
Weather routing via variational methods
Interactive visualisations for the variational polaron problem with Makie.
a python code that uses the randomness of neural network training to find the ground state of a harmonic oscillator and its energy
👀🛡️ Code for the paper “Carefully Blending Adversarial Training and Purification Improves Adversarial Robustness” by Emanuele Ballarin, Alessio Ansuini and Luca Bortolussi (2024)
An analysis and speedup of the FALDOI method for Optical Flow estimation
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