ccclab-bigdata Goto Github PK

als-baseline-subtraction

Asymmetric Least Squares C++ implementation

betatools

Code that enables investigation of beta oscillations in neural data

books

Source code for 100+ books, kept here for quick reference

cdml-neurips2020

This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop at Neural Information Processing Systems (NeurIPS) 2020.

ckbs

Constrained Kalman-Bucy Smoothing

compare-trackings

covariancetoolbox

Covariance toolbox for matlab, including riemannian geometry

dataanabook

MatLab code for Srpinger book 'Advanced Data Analysis in Neuroscience'

deep-learning-topics

dmdlab

Dynamic Mode Decomposition in Python

docstest

ede

EDE code

eeg-datasets

A list of all public EEG-datasets

ensemble-regression

estimated-marginal-means

Estimated marginal (predicted) means from generalized linear mixed effect models in Matlab

external

Repository for external libraries

f-svar

Estimating dynamic connectivity states in neuroimaging data using regime-switching factor models

fastrpca

Matlab code for all variants of robust PCA and SPCP

fsstn

High-Order Synchrosqueezing Transform for Multicomponent Signals Analysis

gemma

Genome-wide Efficient Mixed Model Association

informedgeometry-coupledpendulum

ipsolve

Interior point solver for PLQ densities

kalman-jax

Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX

koopmanmpc_for_flowcontrol

A data-driven framework for control of nonlinear flows with Koopman Model Predictive Control

lmeminr

materials for Linear Mixed Effect Modeling workshop

localization-in-wireless-sensor-networks-evaluation-and-comparison-of-the-optimization-methods

Sensor localization is a main component in any problem related to wireless sensor networks. The knowledge of sensor locations plays a major role in energy optimization, communication protocol designs and data analysis of wireless sensor networks. In this thesis we aim at gathering many of the algorithms introduced recently in the literature for sensor localization and categorize them in several meaningful categories. We also study a particularly interesting optimization framework for finding the location of the sensors using their mutual distances. We introduce the use of simulated annealing based methods for sensor localization as a minimizer of any defined cost function for this purpose. Our simulation results confirm the usefulness of these approaches in practical setups.

lwp_regression_prediction

Local polynomial kernel regression with out od example

macularhole_segmentation3d

manopt

Manopt, a Matlab toolbox for optimization on manifolds

matlab-packages

Some MATLAB packages that I found to be useful