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5g-network-slicing-for-wifi-networks

5G Network Slicing for Wi-Fi Networks

5g3e-dataset

airdl

albumentations

Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

aouedions11.github.io

atic-frontend-app

attack-and-anomaly-detection-in-iot-sensors-in-iot-sites-using-machine-learning-approaches

Attack and Anomaly detection in the Internet of Things (IoT) infrastructure is a rising concern in the domain of IoT. With the increased use of IoT infrastructure in every domain, threats and attacks in these infrastructures are also growing commensurately. Denial of Service, Data Type Probing, Malicious Control, Malicious Operation, Scan, Spying and Wrong Setup are such attacks and anomalies which can cause an IoT system failure. In this paper, performances of several machine learning models have been compared to predict attacks and anomalies on the IoT systems accurately. The machine learning (ML) algorithms that have been used here are Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN). The evaluation metrics used in the comparison of performance are accuracy, precision, recall, f1 score, and area under the Receiver Operating Characteristic Curve. The system obtained 99.4% test accuracy for Decision Tree, Random Forest, and ANN. Though these techniques have the same accuracy, other metrics prove that Random Forest performs comparatively better.

awesome-explainable-graph-reasoning

A collection of research papers and software related to explainability in graph machine learning.

awesome-federated-computing

:books: :eyeglasses: A collection of research papers, codes, tutorials and blogs on Federated Computing/Learning.

awesome-federated-learning

Federated Learning Library: https://fedml.ai

awesome-graph-transformer

Papers about graph transformers.

behavioral-model

The reference P4 software switch

cellular-traffic-analysis

Analysis of real cellular traffic captured on a device

clustered-federated-learning

Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints

cnn-lstm-bilstm-deepcnn-clstm-in-pytorch

In PyTorch Learing Neural Networks Likes CNN(Convolutional Neural Networks for Sentence Classification (Y.Kim, EMNLP 2014) 、LSTM、BiLSTM、DeepCNN 、CLSTM、CNN and LSTM

collaborativefairfederatedlearning

Official implementation of our work "Collaborative Fairness in Federated Learning."

convlstm_pytorch

Implementation of Convolutional LSTM in PyTorch.

cpip

decision-tree-based-blending-method-using-deep-learning-for-network-management

deep-learning-time-series

List of papers, code and experiments using deep learning for time series forecasting

deepconvlstm

Deep learning framework for wearable activity recognition based on convolutional and LSTM recurretn layers

edgecloudsim

EdgeCloudSim: An Environment for Performance Evaluation of Edge Computing Systems

edgefed-marl-mec

failed-ml

Compilation of high-profile real-world examples of failed machine learning projects

fashion-mnist

A MNIST-like fashion product database. Benchmark :point_down:

fedaa

fedda

Source code for 'Dual Attention Based FL for Wireless Traffic Prediction'

federated

A collection of Google research projects related to Federated Learning and Federated Analytics.

federated-learning

federated-learning-1

Everything about Federated Learning (papers, tutorials, etc.) -- 联邦学习