mahmoudmostapha Goto Github PK

asdprediction

comp562

COMP562 - Introduction to Machine Learning [Fall 2018]

deeplearning.ai

Materials from deeplearning.ai course on Coursera

doc2vec

A simple and readable implementation of doc2vec, using Python 3, Keras and TensorFlow.

extensionsindex

Slicer extensions index

groups

isbi_2018_tutorial

ISBI 2018 Tutorial on CXR Anatomy Segmentation

keras-aae

Implementation of Adversarial Autoencoder in Keras

local_eacsf

mfsda

Multivariate Functional Shape Data Analysis (MFSDA) is a Matlab based package for statistical shape analysis. A multivariate varying coefficient model is introduced to build the association between the multivariate shape measurements and demographic information and other clinical variables. Statistical inference, i.e., hypothesis testing, is also included in this package, which can be used in investigating whether some covariates of interest are significantly associated with the shape information. The hypothesis testing results are further used in clustering based analysis, i.e., significant suregion detection. This MFSDA package is developed by Chao Huang and Hongtu Zhu from the BIG-S2 lab.

mfsda_python

Multivariate Functional Shape Data Analysis in Python (MFSDA_Python) is a Python based package for statistical shape analysis. A multivariate varying coefficient model is introduced to build the association between the multivariate shape measurements and demographic information and other clinical, biological variables. Statistical inference, i.e., hypothesis testing, is also included in this package, which can be used in investigating whether some covariates of interest are significantly associated with the shape information. The hypothesis testing results are further used in clustering based analysis, i.e., significant suregion detection. This MFSDA package is developed by Chao Huang and Hongtu Zhu from the BIG-S2 lab.

mfsda_syntheticdata

Synthetic Experiment to Test MFSDA

models

Models and examples built with TensorFlow

oc-nn

Repository for the One class neural networks paper

phd-dissertation

Source Code for my PhD Dissertation

phd-dissertation-1

An archive of my Ph.D. Dissertation

slicer-mfsda

Multivariate Functional Shape Data Analysis in Python (MFSDA_Python) is a Python based package for statistical shape analysis. A multivariate varying coefficient model is introduced to build the association between the multivariate shape measurements and demographic information and other clinical, biological variables.

spharm-pdm

Shape analysis has become of increasing interest to the medical community due to its potential to precisely locate morphological changes between healthy and pathological structures. SPHARM-PDM is a tool that computes point-based models using a parametric boundary description for the computing of Shape analysis.

tan

tensorflow-tutorials

TensorFlow Tutorials with YouTube Videos

torchdiffeq

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

umap

Uniform Manifold Approximation and Projection

vaegan

Keras implementation of the paper "Autoencoding beyond pixels using a learned similarity metric"