Angelos Alexopoulos
  • Home
  • Publications
  • Recent & Upcoming Talks
  • Projects
  • Recent & Upcoming Talks
    • Deep Generative models for fraud detection
    • Causal Inference
    • A Network and Machine Learning Approach to Detect Value Added Tax Fraud
    • Fraud detection in the Greek fuel market by using machine learning methods
    • A machine learning approach to construct quarterly data on intangible investment for Eurozone
  • Publications
    • Gaussian invariance in Markov chain Monte Carlo
    • A Bayesian multivariate factor analysis model for causal inference using time series observational data on mixed outcomes
    • A stochastic dynamical model for epidemic nowcasting and forecasting
    • A machine learning approach to construct quarterly data on intangible investment for Eurozone
    • Networks and machine learning to detect Value Added Tax fraud
    • Variance reduction for Metropolis-Hastings samplers
    • Bayesian prediction of jumps in large panels of time series data
    • Bayesian Variable Selection for Gaussian copula regression models
    • Bayesian forecasting of mortality rates by using latent Gaussian models
  • Projects
  • Blog
    • 🎉 Easily create your own simple yet highly customizable blog
    • 🧠 Sharpen your thinking with a second brain
    • 📈 Communicate your results effectively with the best data visualizations
    • 👩🏼‍🏫 Teach academic courses
    • ✅ Manage your projects
  • Experience
  • Teaching
    • Learn JavaScript
    • Learn Python
  • Projects
    • DETECTIVE

Deep Generative models for fraud detection

Sep 11, 2024·
Angelos Alexopoulos
Angelos Alexopoulos
· 0 min read
Date
Sep 11, 2024 12:00 AM
Event
IOTA Webinar on Generative AI for tax purposes, Budapest, Hungary
Last updated on Sep 11, 2024
Angelos Alexopoulos
Authors
Angelos Alexopoulos
Assistant Professor
Causal Inference Aug 28, 2024 →

© 2024 Angelos Alexopoulos. This work is licensed under CC BY NC ND 4.0

Published with Hugo Blox Builder — the free, open source website builder that empowers creators.