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

The Association of Certified Fraud Examiners estimates in its “GlobalStudy on Occupational Fraud and Abuse 2018”…

Adversarial Learning of Deep fakes in Accounting

Machine learning techniques, and in particular deep neural networks, created advances across a diverse range of…

Utilizing Machine Learning Techniques to Reveal VAT Compliance Violations in Accounting Data

Research has shown that little attention is being paid to Value Added Tax (VAT) issues. There…

Accounting Journal Reconstruction with Variational Autoencoders and Long Short-term Memory Architecture

Deep learning is used to learn machines how to reconstruct journal entries. We developed basic models…

A Semi-Supervised Machine Learning Approach to Detect Anomalies in Big Accounting Data

Anomaly detection in large scale accounting data is one of the long-standing challenges in the financial…

Autoencoder Neural Networks versus External Auditors: Detecting Unusual Journal Entries in Financial Statement Audits

Most public companies are required by law to have their financial statements audited annually by external…

Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation

We propose a simple solution to use a single Neural Machine Translation (NMT) model to translate…

A Neural Chatbot with Personality

Conversational modeling is an important task in natural language processing as well as machine learning. Previously,…

A review of KDD99 dataset usage in intrusion detection and machine learning between 2010 and 2015

KDD99 dataset is more than 15 years old, it is still widely used in academic research.…

Data Sanity Check for Deep Learning Systems via Learnt Assertions

SaneDL is a tool that provides systematic data Sanity check for Deep Learning-based Systems. SaneDL serves…