323 Open source projects that are alternatives of or similar to Midas

A Deep Graph-based Toolbox for Fraud Detection in TensorFlow 2.X

A Deep Graph-based Toolbox for Fraud Detection

An Unsupervised Graph-based Toolbox for Fraud Detection

Clojure library for querying Apache TinkerPop graphs

log anomaly detection toolkit including DeepLog

STUMPY is a powerful and scalable Python library for modern time series analysis

A semantic diff utility and library for tree-like files such as JSON, JSON5, XML, HTML, YAML, and CSV.

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

An End-to-end Outlier Detection System

Source code for Skip-GANomaly paper

[5 FPS - 150 FPS] Learning Deep Features for One-Class Classification (AnomalyDetection). Corresponds RaspberryPi3. Convert to Tensorflow, ONNX, Caffe, PyTorch. Implementation by Python + OpenVINO/Tensorflow Lite.

Log-based Impactful Problem Identification using Machine Learning [FSE'18]

Anomaly detection for streaming time series, featuring automated model selection.

Data Structures with Go Language

GAP Benchmark Suite

Foremast adds application resiliency to Kubernetes by leveraging machine learnt patterns of application health to keep applications healthy and stable

A collection of common algorithms and data structures implemented in java, c++, and python.

🐙 🐙图形学论文实现

Log Anomaly Detection - Machine learning to detect abnormal events logs

modular and modern graph-theory algorithms framework in Java

Common data structures and algorithms implemented in JavaScript

Hierarchical Graph Pooling with Structure Learning

💥 Interactive and colorful 🎨 graph theory tutorials made using d3.js ⚡️

Real-World Anomaly Detection in Surveillance Videos

Graph-Based Data Science: an abstraction layer in Python for building knowledge graphs, integrated with popular graph libraries – atop Pandas, RDFlib, pySHACL, RAPIDS, NetworkX, iGraph, PyVis, pslpython, pyarrow, etc.

DeepWalk implementation in C++

BERT, AWS RDS, AWS Forecast, EMR Spark Cluster, Hive, Serverless, Google Assistant + Raspberry Pi, Infrared, Google Cloud Platform Natural Language, Anomaly detection, Tensorflow, Mathematics

A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.

A robust, and flexible open source User & Entity Behavior Analytics (UEBA) framework used for Security Analytics. Developed with luv by Data Scientists & Security Analysts from the Cyber Security Industry. [PRE-ALPHA]

Hastic data management server for labeling patterns and anomalies in Grafana

CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances (NeurIPS 2020)

Latent space autoregression for novelty detection.

depthmapX is a multi-platform Spatial Network Analysis Software

Open-source framework to detect outliers in Elasticsearch events

Python implementation of TextRank for phrase extraction and summarization of text documents

Source Code for the Book Classic Computer Science Problems in Swift

Deep Learning sample programs using PyTorch in C++

Repository for the Deep One-Class Classification ICML 2018 paper

图卷积神经网络 Graph Convolutional Network with Keras

A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.

A Graph Algorithms Visualizer built using React, Typescript and Styled Components.

PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)

Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

SparklingGraph provides easy to use set of features that will give you ability to proces large scala graphs using Spark and GraphX.

Python implementation of frequent subgraph mining algorithm gSpan. Directed graphs are supported.

R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.

A curated list of awesome anomaly detection resources

Abnormal Event Detection in Videos using SpatioTemporal AutoEncoder

Reference implementation of the paper VERSE: Versatile Graph Embeddings from Similarity Measures

🍇 A C++ library for parallel graph processing 🍇

Awesome Procedures On Cypher for Neo4j - codenamed "apoc"                     If you like it, please ★ above ⇧            

A Spark/Scala implementation of the isolation forest unsupervised outlier detection algorithm.

Unsupervised anomaly detection with generative model, keras implementation

Implementation of Visual Feature Attribution using Wasserstein GANs (VAGANs, https://arxiv.org/abs/1711.08998) in PyTorch

DSA-Self Paced With Doubt Assistance Course Solutions in Python (Python 3)

Streaming Anomaly Detection Framework in Python (Outlier Detection for Streaming Data)

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

List of tools & datasets for anomaly detection on time-series data.

Anomaly detection for temporal data using LSTMs

new layout algorithms for network visualizations in R