variational-method
There are 43 repositories under variational-method topic.
netket/netket
Machine learning algorithms for many-body quantum systems
FEniCS/ffcx
Next generation FEniCS Form Compiler for finite element forms
FEniCS/ufl
UFL - Unified Form Language
plainerman/Variational-Doob
Lagrangian formulation of Doob's h-transform allowing for efficient rare event sampling
icemiliang/pyvot
A Python implementation of Monge optimal transportation
PDAF/PDAF
Parallel Data Assimilation Framework
UMD-AOSC/DA_Tutorial
This is a 'hands-on' tutorial for the RIKEN International School on Data Assimilation (RISDA2018).
gher-uliege/DivaPythonTools
Interface to run Diva software tool (spatial interpolation).
netket/netket_fidelity
Projected time-dependent Variational Monte Carlo (p-tVMC) method based on infidelity optimization for variational simulation of quantum dynamics.
variPEPS/variPEPS_Python
variPEPS -- Versatile tensor network library for variational ground state simulations in two spatial dimensions
yumengch/pyPDAF
A Python interface to parallel data assimilation framework - pyPDAF
comp-physics/NISQ-Quantum-CFD
CFD solve on a current quantum computer
simoneparisotto/Variational-Osmosis-for-Non-Linear-Image-Fusion
Variational Osmosis for Non-Linear Image Fusion
tcompa/BoseHubbardGutzwiller
Gutzwiller variational approach for the Bose-Hubbard model, with simulated-annealing optimization
CFEL-CMI/FlowBasis
FlowBasis: Variational solutions of perturbed quantum harmonic oscillator problems via augmented basis sets.
emaballarin/CARSO
👀🛡️ 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)
gudovskiy/contextflow
Official PyTorch code for UAI 2024 paper "ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-variable Context Encoding"
Tiernan8r/variational_principle
Implementation of the Variational Method for Quantum Mechanics in python.
daniprec/hybrid_ivp
Weather routing via variational methods
mendzmartin/FEMTISE.jl
Variational approximation by Gridap package to resolve T.I.S.E. in Julia
yvesantonio/Data_Assimilation
Advanced Data Assimilation Algorithms and Methods
FlowRegSuite/variational_aligner
Toolbox for fast, variational 1D alignment
quadrivecteur/minimization
a python code that uses the randomness of neural network training to find the ground state of a harmonic oscillator and its energy
s-nakashita/pydpac
Python scripts for trying various data assimilation algorithms with simple toy models
fperezgamonal/faldoi-ipol
An analysis and speedup of the FALDOI method for Optical Flow estimation
Neutrino155/PolaronMakie.jl
Interactive visualisations for the variational polaron problem with Makie.
QcmPlab/VCA
Variational Cluster Approximation based on lanczos exact diagonalization.
FlowRegSuite/variational_aligner_IJ
ImageJ and Fiji Plugin for fast, variational 1D alignment of multichannel linescan data
gher-uliege/Diva-User-Guide
User Guide of the Data Interpolating Variational Analysis (Diva) software tool
ibipul/segmentation-2Dsnakes-wt-interactive-control
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
lu-kie/HOMS_SignalProcessing
Joint smoothing and partitioning of one-dimensional signals and time series with higher order Mumford-Shah models
lu-kie/PALMS_ImagePartitioning
Image partitioning (color/gray/multichannel) based on the piecewise affine-linear Mumford-Shah model (aka the affine-linear Potts model)
apallath/pyves
Variationally enhanced sampling for single-particle langevin dynamics with neural network bias potentials and path collective variables. Based on OpenMM + PyTorch.
computeVision/optical_flow
summary of current machine learning appraoches and optical flow
MauroCE/Dissertation
Third year mathematics dissertation on variational, laplace and mcmc approximations of bayesian logistic regression