ahmeddeladly

arch

ARCH models in Python

assignment4-calcium_imaging_analysis

BG_selectivity

Experiments on a computational model of the basal ganglia.

CaImAn

Computational toolbox for large scale Calcium Imaging Analysis, including movie handling, motion correction, source extraction, spike deconvolution and result visualization.

Calcium-imaging-data-analysis

In this project our aim is to study difference in neuronal activity between normal and genetically modified mice with epileptic behavior. To facilitate, here we are designing and implementing analysis pipeline to analyze ca2+ data.

GP_algorithm

Implementation of the Grassberger-Procaccia algorithm to estimate the Correlation Dimension of a set of points

hmm-mne

Hidden Markov Modelling of M/EEG data.

Hydra-Neural-Activity-Analysis

Single-cell neural activity processing toolkit for calcium imaging recordings of deformable organisms

kCSD-python

Kernel Current Source Density

machine-learning

Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression

ahmeddeladly/BG_selectivity

Experiments on a computational model of the basal ganglia.

ahmeddeladly/time_series_handbook

ahmeddeladly/ahmeddeladly.github.io

ahmeddeladly/Bayesian_Statistical_Modeling_with_Stan_R_and_Python

Kentaro Matsuura (2023). Bayesian Statistical Modeling with Stan, R, and Python. Springer, Singapore.

ahmeddeladly/BioImageAnalysisNotebooks

Python Jupyter notebooks for BioImageAnalysis, GPU-accelerated image processing, bio-image data science and more

ahmeddeladly/BookCode_Edition1

ahmeddeladly/CAMBAM_Workshop_Neuron_Excitability

Jupyter Notebooks for 2023 CAMBAM Workshop on Neuronal Excitability

ahmeddeladly/Causal-Inference-and-Discovery-in-Python

Causal Inference and Discovery in Python by Packt Publishing

ahmeddeladly/causalimpact

Python port of CausalImpact R library

ahmeddeladly/causallib

A Python package for modular causal inference analysis and model evaluations

ahmeddeladly/curriculum

ahmeddeladly/dartbrains

This repository is a Python package with all of the functions and python libraries required for the Dartmouth fMRI Analysis Course taught by Prof Luke Chang, PhD.

ahmeddeladly/DataSciPy2022

Neural Data Science with Python course material

ahmeddeladly/deeptime

Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation

ahmeddeladly/EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) isalgorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

ahmeddeladly/emcee

The Python ensemble sampling toolkit for affine-invariant MCMC

ahmeddeladly/facemap

matlab/python GUI for unsupervised video analysis of rodent behavior (capable of processing multiple camera views)

ahmeddeladly/GRAPL

GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference

ahmeddeladly/hmm-lds-em-algorithm

Estimate Hidden Markov Models (HMM) and Linear Dynamical Systems (LDS)

ahmeddeladly/ModelingNeuralCircuits

PDF and Code to accompany the textbook "Modeling Neural Circuits Made Simple"

ahmeddeladly/NeuralDataSciPy2023

All information of the Neural Data Science with Python course of the Neuroscience Master program at Université Paris Cité.

ahmeddeladly/neuronaldynamics-exercises

Python exercises accompanying the book "Neuronal Dynamics"

ahmeddeladly/pykalman

Kalman Filter, Smoother, and EM Algorithm for Python

ahmeddeladly/pymc-resources

PyMC educational resources

ahmeddeladly/pyprobml

Python code for "Probabilistic Machine learning" book by Kevin Murphy

ahmeddeladly/relataly-public-python-tutorials

Beginner-friendly collection of Python notebooks for various use cases of machine learning, deep learning, and analytics. For each notebook there is a separate tutorial on the relataly.com blog.

ahmeddeladly/replay_identification

A semi-latent state-space model that combines movement, LFP, and ensemble spiking information to identify periods of replay and decode its content in real time. Long Tao et al., unpublished.

ahmeddeladly/ssm

Bayesian learning and inference for state space models

ahmeddeladly/sysidentpy

A Python Package For System Identification Using NARMAX Models

ahmeddeladly/Whalen_et_al_2021