Taecyeon's Stars
PRML/PRMLT
Matlab code of machine learning algorithms in book PRML
kumar-shridhar/PyTorch-BayesianCNN
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
itbooks1024/books-pdf
程序员必看的经典书籍，编程电子书下载，附带pdf下载链接，包括C，C++，Java，Python，Linux，Go，数据结构与算法，人工智能，计算机基础，面试，设计模式，数据库，前端等
Freemanzxp/GBDT_Simple_Tutorial
python实现GBDT的回归、二分类以及多分类，将算法流程详情进行展示解读并可视化，庖丁解牛地理解GBDT。Gradient Boosting Decision Trees regression, dichotomy and multi-classification are realized based on python, and the details of algorithm flow are displayed, interpreted and visualized to help readers better understand Gradient Boosting Decision Trees
maziarraissi/HPM
Hidden physics models: Machine learning of nonlinear partial differential equations
kennydl/Reinforcment-Learning-With-Q-Learning
kanechew/Power-Systems-Optimization
Implementation of Optimization Techniques for Economic Dispatch of Power Systems
tony-psq/QRMGM_KDE
A probabilistic forecasting method based on Quantile Regression Minimal Gated Memory Network and Kernel Density Estimation.
zhangchunlei0813/Nonconvex-localization
Simulations for Paper Sensor Network Event Localization via Non-convex Non-smooth ADMM and Augmented Lagrangian Methods
rort1989/BH-HSMM
Bayesian Hierarchical Hidden semi-Markov Model
SINTEF-Energy-Wind/STAS-WPP
A unified state-space model of a wind power plant, for system dynamics, optimization, and control. Developed for Gnu Octave.
Sohan-Rai/Multivariate-windspeed-prediction-using-ANN
Artificial neural networks model on matlab to predict wind speed. Data on wind speed, humidity, temperature and wind direction was obtained from Bagalkot wind farm, Karnataka, India, in the year 2014.
mtanveer1/Pinball-Loss-Twin-Support-Vector-Clustering
zjph602xtc/Quantile_reg
Adaptive algorithm for quantile regression
DannyMerkx/ACO
Ant Colony Optimisation implementation for learning Bayesian Network structures from data
jiaqg/Q-learning
Q learning matlab code
jieunbyun/GitHub-MBN-DM-code
Accompanying code of RESS paper "Efficient Probabilistic Multi-Objective Optimization of Complex Systems Using Matrix-based Bayesian Network" (2020). doi: https://doi.org/10.1016/j.ress.2020.106899
tyger2020/HAWC
HAWC - Hybrid Algorithms for Wind-power Computation - uses machine learning to improve the accuracy of wind turbine power output predictions.
shuangxu96/VBR
Variational Bayesian Complex Network Reconstruction
Harpreet221295/Markov-Chain-Monte-Carlo-Sampling-Methods-for-Approximate-Bayesian-Inference-on-Markov-Networks
MotokiShiga/sparse-additive-cde
An estimation method of a conditional probability density function
T-Obuchi/AMPR_lasso_matlab
Bootstrap resampling is used to estimate confidence interval of variables in Lasso (some famous methods are bolasso and stability selection). This MATLAB package performs this in an efficient manner by conducting the resampling in a semi-analytic manner, enabling to avoid numerical resampling. Python translation is available: https://github.com/T-Obuchi/AMPR_lasso_python
wang19940624/metaheuristics-for-economic-dispatch-in-power-system
aristotelis86/Hybrid_Kalman-Bayes_filter
Hybrid filter for post-process improvement of forecasts provided by NWP (Numerical Wind/Wave Prediction) models.
dlinzner-bcs/ctbn-toolbox
A toolbox for exact and approximate inference in continuous-time Bayesian networks
ganeshsankaran/matlab-ap-statistics
M-files for distribution functions, confidence intervals, and hypothesis tests
gaspardbb/astreos
Predicting day-ahead wind farms production, using CNR's data - challengedata.ens.fr
sarah-white/QQplots-with-confidence-intervals
Make quantile-quantile plots (and normalized plots) with confidence intervals, to compare multiple datasets to one reference dataset.
feuerchop/CausalNet4IDS
Causality discovery toolbox using Copula Bayesian Networks
wang19940624/Advanced-Power-System-Operation-
M files for different techniques for ecomomic dispatch in Power Systems