GitPlanet

Cheap and reliable Node.js hosting starts at $3/month, and $1/month static HTML hosting

Created with love in Canada, visit hostnodejs.com today

Feel like to post an Ad? Learn Details
All Projects → GitiHubi → deepAD

GitiHubi / deepAD

Licence: other
Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the KDD'19 Workshop on Anomaly Detection in Finance that will walk you through the detection of interpretable accounting anomalies using adversarial autoencoder neural networks. The majority of the lab content is based on J…

Programming Languages

Jupyter Notebook
11667 projects

Labels

deep-learningaccountingpytorchfraud-preventionfraud-detectionanomaly-detectionadversarial-autoencodersforensic-accounting

Projects that are alternatives of or similar to deepAD

DGFraud-TF2
A Deep Graph-based Toolbox for Fraud Detection in TensorFlow 2.X
Stars: ✭ 84 (+29.23%)
Mutual labels:  fraud-prevention, fraud-detection, anomaly-detection
benfordslaw
benfordslaw is about the frequency distribution of leading digits.
Stars: ✭ 29 (-55.38%)
Mutual labels:  fraud-detection, anomaly-detection
MemStream
MemStream: Memory-Based Streaming Anomaly Detection
Stars: ✭ 58 (-10.77%)
Mutual labels:  fraud-detection, anomaly-detection
CARE-GNN
Code for CIKM 2020 paper Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters
Stars: ✭ 121 (+86.15%)
Mutual labels:  fraud-prevention, fraud-detection
Feature-Engineering-for-Fraud-Detection
Implementation of feature engineering from Feature engineering strategies for credit card fraud
Stars: ✭ 31 (-52.31%)
Mutual labels:  fraud-detection, anomaly-detection
Pyod
A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
Stars: ✭ 5,083 (+7720%)
Mutual labels:  fraud-detection, anomaly-detection
xgboost-smote-detect-fraud
Can we predict accurately on the skewed data? What are the sampling techniques that can be used. Which models/techniques can be used in this scenario? Find the answers in this code pattern!
Stars: ✭ 59 (-9.23%)
Mutual labels:  fraud-prevention, fraud-detection
IDVerification
"Very simple but works well" Computer Vision based ID verification solution provided by LibraX.
Stars: ✭ 44 (-32.31%)
Mutual labels:  fraud-prevention, fraud-detection
predict-fraud-using-auto-ai
Use AutoAI to detect fraud
Stars: ✭ 27 (-58.46%)
Mutual labels:  fraud-prevention, fraud-detection
SentryPeer
A distributed peer to peer list of bad actor IP addresses and phone numbers collected via a SIP Honeypot.
Stars: ✭ 108 (+66.15%)
Mutual labels:  fraud-prevention, fraud-detection
Misp
MISP (core software) - Open Source Threat Intelligence and Sharing Platform
Stars: ✭ 3,485 (+5261.54%)
Mutual labels:  fraud-prevention, fraud-detection
Deepai
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.
Stars: ✭ 104 (+60%)
Mutual labels:  accounting, anomaly-detection
suspicidy
Suspicidy aims to detect suspicious web requests
Stars: ✭ 13 (-80%)
Mutual labels:  fraud-prevention, fraud-detection
GMRPD
A Ground Mobile Robot Perception Dataset, IEEE RA-L & IEEE T-CYB
Stars: ✭ 30 (-53.85%)
Mutual labels:  anomaly-detection
kubervisor
The Kubervisor allow you to control which pods should receive traffic or not based on anomaly detection.It is a new kind of health check system.
Stars: ✭ 35 (-46.15%)
Mutual labels:  anomaly-detection
anompy
A Python library for anomaly detection
Stars: ✭ 13 (-80%)
Mutual labels:  anomaly-detection
out-of-distribution-detection
The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks
Stars: ✭ 117 (+80%)
Mutual labels:  anomaly-detection
pytod
TOD: GPU-accelerated Outlier Detection via Tensor Operations
Stars: ✭ 131 (+101.54%)
Mutual labels:  anomaly-detection
Hyperspectral-Anomaly-Detection-LSUNRSORAD-and-LSAD-CR-IDW-
This is the code for the paper nemed 'Anomaly Detection for Hyperspectral Imagery Based on the Regularized Subspace Method and Collaborative Representation'
Stars: ✭ 22 (-66.15%)
Mutual labels:  anomaly-detection
kenchi
A scikit-learn compatible library for anomaly detection
Stars: ✭ 36 (-44.62%)
Mutual labels:  anomaly-detection
View All Similar Projects ➔

Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks

License: GPL v3

Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the 2nd KDD'19 Workshop on Anomaly Detection in Finance that will walk you through the detection of interpretable accounting anomalies using adversarial autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

The workshop details are available via the KDD'19 workshop webpage under the following external link.

Running the Notebook

Open In Colab

Reference

Autoencoder

The lab is inspired by our work "Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks" by Marco Schreyer, Timur Sattarov, Christian Schulze, Bernd Reimer and Damian Borth.

The publication is available via arXiv under the following link: https://arxiv.org/abs/1908.00734 .

Questions?

Please feel free to get in touch by opening an issue report, submitting a pull request, or sending us an email.

Disclaimer

Opinions expressed in this work are solely those of the authors, and do not necessarily reflect the view of Deutsche Bundesbank or PricewaterhouseCoopers (PwC) International Ltd. and its network firms.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].