Minimum Probability Flow-Boltzmann Machine Learning (MPF-BML) standalone GUI-based application for the inference of maximum entropy distribution parameters
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Updated
Dec 18, 2019
Minimum Probability Flow-Boltzmann Machine Learning (MPF-BML) standalone GUI-based application for the inference of maximum entropy distribution parameters
Simulation of the Potts model for a university course in Monte Carlo simulations
course project of Probability and Stochastic Processes (2) of EE, Tsinghua University.
Image denoising using Markov random fields.
Task Assignment with Potts Model
2D potts model implementation (equals a 2D ising model when spins are limited to 2 states)
Exploration of phase transition in classical 2D, q={2,3,4,5,6} Potts model with Machine Learning
PXO (Poly-XTAL Operations). Generate, analyze and export complex 2D space partitions like metallic grain structures
Wolff algorithm for the q Potts model.
Joint smoothing and partitioning of one-dimensional signals and time series with higher order Mumford-Shah models
This repository is for regenerating the results in the paper.
Modelling of recrystallization of single phase material
Code for Monte-Carlo simulation of q-state potts model.
A demo to simulate 2D spin lattices with different shapes, boundary conditions, models and algorithms
Simulation of space-embedded molecular aggregates using Potts model
Computer project of Random Simulation method, MCMC simulation of Potts model
Unsupervised multilabel image segmentation (color/gray/multichannel) based on the Potts model (aka piecewise constant Mumford-Shah model)
A highly modular simulation framework of Monte-Carlo methods, based on the Ising Model in a 2D spin lattice. Producing results for the macroscopic properties of the system via simulation and bootstrapping. A few commonly used algorithms are built-in. Model generalizations and additional algorithms can be implemented.
Running SPPARKS (Stochastic Parallel Particle Kinetic Simulator) on HPC system
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