Predictive and generative neural networks

Machine learning applications based on neural networks have been flourishing over the years. In this report, we explore how to generate and predict random variables using neural networks, starting from well known methods, namely the inverse transform method and maximum likelihood techniques, then e...

Full description

Bibliographic Details
Main Author: Chan, Keefe
Other Authors: Frederique Elise Oggier
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/148514
Description
Summary:Machine learning applications based on neural networks have been flourishing over the years. In this report, we explore how to generate and predict random variables using neural networks, starting from well known methods, namely the inverse transform method and maximum likelihood techniques, then evolving towards scenarios where the need of predictive and generative neural networks arises