Matlab code for machine learning algorithms in book PRML
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Updated
Jan 3, 2020 - MATLAB
MATLAB is a high-performance language developed by MathWorks for technical computing, visualization, and programming. It is written in C, C++, Java and available for Windows, macOS, and Linux. Generally used by engineers and scientists in industry and academics for data analysis, signal processing, optimization and many other types of scientific computations.
Matlab code for machine learning algorithms in book PRML
Code repo for realtime multi-person pose estimation in CVPR'17 (Oral)
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Implements face recognition algorithms for MATLAB/GNU Octave and Python.
PST or Phase Stretch Transform is an operator that finds features in an image. PST implemented using MATLAB here, takes an intensity image I as its input, and returns a binary image out of the same size as I, with 1's where the function finds sharp transitions in I and 0's elsewhere.
Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos
A curated list of awesome neuroscience libraries, software and any content related to the domain.
🤖 MatLab/Octave examples of popular machine learning algorithms with code examples and mathematics being explained
Some of the source files have a casadi_ prefix, but most don't. For consistency, we should add it everywhere, especially since we have already added them to the include guards.
We should check if the user is exporting from a version of MATLAB which supports the language being exported due to the following scenario:
solution of exercises of the book "probabilistic robotics"
pierre, thanks for your work on this really fantastic toolbox - and making it available here. we've started using it in my lab and it has quickly proven to be super-useful.
i have also been encouraging colleagues to re-think they way they do their plotting in matlab with gramm.
you mentioned in a separate thread that developing some tutorials + walk-throughs and a bit more documentation
As discussed with Stefan and Malina, we should extend and upgrade the seven example to a tutorial. As part of that, we should implement an ft_steadystatesimulation function.
Armadillo: fast C++ library for linear algebra & scientific computing - http://arma.sourceforge.net
Similarly to LaTeX table export we can also have simple CSV export so that data can be imported to spreadsheet editor.
Deep Recurrent Neural Networks for Source Separation
Highly comparative time-series analysis code repository
Bitcoin price prediction algorithm using bayesian regression techniques
Code for "Toward Convolutional Blind Denoising of Real Photographs", CVPR 2019
Learning a Single Convolutional Super-Resolution Network for Multiple Degradations (CVPR, 2018)
TOMM2017 A Discriminatively Learned CNN Embedding for Person Re-identification
Curvature Filters are efficient solvers for Variational Models
Efficient, transparent deep learning in hundreds of lines of code.
Add config options to offline charts similar to the python api. This will allow customizations such as the removal of the modebar.
DeepSqueak: A Deep Learning Based System for Quantification of Ultrasonic Vocalizations
Created by Cleve Moler
Released 1984
@egeerardyn spotted that grid options are currently not handled. It should be straight forward to implement. As such I add this issue to track this feature request and so we do not forget about it.