Topic: "multi-layer-networks"
FabioDainese/Networks_in_Economics_and_Social_Science
Various tasks related to graphs and networks theory
Language: MATLAB - Size: 19.4 MB - Last synced at: almost 2 years ago - Pushed at: about 5 years ago - Stars: 3 - Forks: 1
ftudisco/node_layer_eigenvector_centrality
Code used for the paper "Node and layer eigenvector centralities for multiplex networks", Tudisco, Arrigo, Gautier, SIAM J. Appl. Math 2017
Language: Matlab - Size: 19.5 KB - Last synced at: about 2 years ago - Pushed at: about 7 years ago - Stars: 3 - Forks: 0
uzunb/Artificial-Neural-Network-GUI
Classification is made in 2-dimensional space with artificial neural networks learning rules. Perceptron and Delta learning rules are implemented in different layers.
Language: C++ - Size: 974 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 2 - Forks: 0
ftudisco/multi-dimensional-hits
Code used for the paper "Multi-dimensional HITS: An always computable ranking for temporal multi-layer directed networks", Arrigo, Tudisco, 2018
Language: Matlab - Size: 24.7 MB - Last synced at: about 2 years ago - Pushed at: about 7 years ago - Stars: 2 - Forks: 0
Develop-Packt/Deep-Neural-Networks-with-Keras
Experiment with Neural Network architectures to build and evaluate both single and multi-layer sequential models in Keras
Language: Jupyter Notebook - Size: 1.76 MB - Last synced at: about 2 years ago - Pushed at: about 5 years ago - Stars: 1 - Forks: 2
WalkingBread/multi-layer-neural-network
Lightweight multi-layer neural network library implemented in pure javascript.
Language: JavaScript - Size: 6.84 KB - Last synced at: over 1 year ago - Pushed at: about 6 years ago - Stars: 1 - Forks: 0
jcasasr/CVC_BrainNetsGNNs
we present a comparative study of various methodologies for processing brain network data with the aim of classifying subjects using Graph Neural Networks (GNNs). Specifically, we explore different strategies for constructing informative graph representations to distinguish people with multiple sclerosis (MS) from healthy controls.
Language: Python - Size: 30.3 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
richardRadli/Multi_Phase_Deep_Random_Neural_Network
Implementation of papers: Rádli, R., & Czúni, L.: Deep Randomized Networks for Fast Learning (2023), Iteratively increasing randomized networks (2024)
Language: Python - Size: 616 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0
GoncaloVCorreia/Epilepsy-Detection-and-Prediction
The main goal of this work is to build and train multilayer NNs, train autoencoders to reduce the number of features for the classifiers and build and train deep networks (CNN and LSTM) for predicting or detecting the seizures.
Language: MATLAB - Size: 15 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
kyaiooiayk/Neural-Networkds-NNs
Notes, tutorials, code snippets and templates focused on NNs for Machine Learning
Language: Jupyter Notebook - Size: 1.17 MB - Last synced at: 5 months ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
jiny419/2019-1-AI_grand_challenge
AI-grand_challenge
Language: Jupyter Notebook - Size: 3.74 MB - Last synced at: almost 2 years ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0
umangrmehta/image-orientation-classifier
Identifying Image Orientation using Supervised Machine Learning Models of k-Nearest Neighbors, Adaboost and Multi-Layer Feed-Forward Neural Network trained using Back-Propagation Learning Algorithm
Language: Python - Size: 6.83 MB - Last synced at: about 1 year ago - Pushed at: over 7 years ago - Stars: 0 - Forks: 1
