mata62n Goto Github PK
Name: MATH
Type: Organization
Bio: Applied Mathematics, Modeling, and Statistics
Location: ECUT
Name: MATH
Type: Organization
Bio: Applied Mathematics, Modeling, and Statistics
Location: ECUT
Trained A Convolutional Neural Network To Play 2048 using Deep-Reinforcement Learning
We propose a distributed computing framework, based on a divide and conquer strategy and hierarchical modeling, to accelerate posterior inference for high-dimensional factor models. Our approach distributes the task of high-dimensional covariance matrix estimation to multiple cores, solves each subproblem separately via a latent factor model, and then combines these estimates to produce a globale estimate of the covariance matrix. The MATLAB code is available for public use. The paper is available at https://arxiv.org/pdf/1612.02875.pdf.
Fast and embedded solvers for nonlinear optimal control
AcATaMa is a Qgis plugin for Accuracy Assessment of Thematic Maps
Implement the JASA paper "Adaptive Thresholding for Sparse Covariance Matrix Estimation"
This Matlab package solves the sparse and low-rank covariance matrix estimation.
Advanced Technique for Curve Fitting
Datasets for the 6th Edition of the book Applied Multivariate Statistical Analysis by Richard Johnson and Dean Wichern
Learning Vector Quantization - Artificial Neural Network
A C++ scientific library for mathematical programming,data fitting and solving nonlinear equations
A curated list of awesome multi-objective optimization research resources.
An R package for Bayesian structural equation modeling
Black-Box Multi-Objective Optimization Benchmarking Platform
solves the steady (time-independent) viscous Burgers equation using a finite difference discretization of the conservative form of the equation, and then applying Newton's method to solve the resulting nonlinear system
This is the realdata for our paper titled as "Robust Sparse Covariance Matrix Estimation for Compositional Data"
A Nonlinear Least Squares Minimizer
A large scale non-linear optimization library
Semidefinite Programming for Nonlinear Chance Optimization
CmdStan, the command line interface to Stan
Covariance Matrix Robust Estimation and Random Matrix Theory Filtering
Image segmentation is the process of partitioning a digital image into multiple segments. The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze [1]. Image segmentation is typically used to locate objects and boundaries in images. Segmentation should stop when the Region of Interest (ROI) in an application have been isolated. An example is, if the image application aims to recognize the iris in an eye image, then the iris in the eye image is the required ROI. Segmentation extracts the Regions of Interest (ROI) from the image to form a similar region by classifying pixels on some basis to group them into a region of similarity. project implemented as windows standalone application
Resources for the book "Complex Networks: A Networking and Signal Processing Perspective"
Complex Nonlinearities for Audio Signal Processing
Confusion matrix for supervised classification
Monte Carlo estimation of parameter uncertainty from parameter covariance matrix for AVHRR satellite harmonisation data
Estimation of the covariance matrix for analyzing heterogeneity in cryo_EM data
Code for extracting multi-scale LBP features and geometric features of human face point cloud, then estimating covariance matrix from the fusion of these feature before classification.
This is the code that generates the figures in the paper titled "Covariance Matrix Estimation for Massive MIMO" authored by Karthik Upadhya and Sergiy A. Vorobyov and published in IEEE Signal Processing Letters, vol. 25, no. 4, pp. 546-550, April 2018.
Covariance Matrix Estimation via Factor Models
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.