Minimum-Probability-Flow-Learning
MPF estimator
This project provides Matlab implementations of Minimum Probability Flow learning for parameter estimation in probabilistic models.
Matlab code implementing Minimum Probability Flow Learning.
68 stars
7 watching
15 forks
Language: Matlab
last commit: about 10 years ago
Linked from 1 awesome list
Related projects:
Repository | Description | Stars |
---|---|---|
pouyamghari/pof-mkl | An implementation of an online federated learning algorithm with multiple kernels for personalized machine learning | 0 |
rlouf/mcx | Tools and methods for Bayesian deep learning using probabilistic programming. | 327 |
phdp/mlbop | The codebase provides MATLAB implementations of machine learning concepts from S. Theodoridis' book | 66 |
michaelchughes/npbayeshmm | Software toolbox for Bayesian inference on sequential data using Markov chain Monte Carlo methods. | 79 |
xidongwu/federated-minimax-and-conditional-stochastic-optimization | This project presents optimization techniques for federated learning and minimax games in the context of machine learning | 0 |
jpzwolak/qflow-suite | A machine learning framework for training models on quantum dot data | 38 |
mostafa-samir/how-machine-learning-works | An implementation of Manning Publications' How Machine Learning Works book in Python using Jupyter Notebook | 4 |
pengskr/mpc | This project implements a Model Predictive Control (MPC) system in MATLAB. | 107 |
minimaxir/automl-gs | Automates machine learning model creation and optimization for complex datasets | 1,856 |
johannespfeifer/particle_filtering | Example code for implementing particle filtering and smoothing in MATLAB | 42 |
nelsonupenn/pmls-matlab-guide | A comprehensive guide to physical modeling using MATLAB | 37 |
pgm-lab/inferpy | A high-level API for probabilistic modeling with a focus on ease of use and scalability | 148 |
matthewpeterkelly/particleswarmoptimization | An optimization algorithm implementation in Matlab. | 82 |
locuslab/e2e-model-learning | Develops an approach to learning probabilistic models in stochastic optimization problems | 201 |
hiroyuki-kasai/sgdlibrary | A collection of stochastic optimization algorithms for large-scale machine learning problems | 220 |