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An adversarial example library for constructing attacks, building defenses, and benchmarking both
Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
Algorithms for outlier, adversarial and drift detection
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning mode…
Implementation of simple autoencoders networks with Keras
Repo of simple adversarial examples on vanilla neural networks trained on MNIST
PySpark solution to the NSL-KDD dataset: https://www.unb.ca/cic/datasets/nsl.html
Network intrusions classification using algorithms such as Support Vector Machine (SVM), Decision Tree, Naive Baye, K-Nearest Neighbor (KNN), Logistic Regression and Random Forest.
Autoencoders using Keras
The same small networks implemented in different frameworks
This is the implementation of Semi-supervised Anomaly Detection using AutoEncoders
The purpose of this repository is to demonstrate the steps of processing CICIDS2017 dataset using machine learning algorithms.
Learning representations for RL in Healthcare under a POMDP assumption
A Tutorial on Deep Reinforcement Learning in PyTorch
Official implementation of (CVPR 2022 Oral) Towards Practical Deployment-Stage Backdoor Attack on Deep Neural Networks.
Pytorch implementation of GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection
Implementation of Neural Machine Translation by jointly learning to align and translate
Classification of colorectal cancer histology into 8 classes
A simple TensorFlow 2 implementation of ResNet-18
Reproduction of cw attack on pytorch with corresponding MNIST model
Predict whether income exceeds $50K/yr based on census data of the "Adult Dataset". Also known as "Census Income" dataset.
Adversarial attacks - Time-Series data - LSTM - Regression - Classification
SVM,Machine Learning, Adversarial Attack
Convolutional autoencoder walkthrough on the MNIST dataset. Builds upon the original keras blog post.