Data-Centric AI: Tabular Data Synthesis with Deep Generative Models

About this item

Title

Data-Centric AI: Tabular Data Synthesis with Deep Generative Models

Content partner

Victoria University of Wellington

Collection

Open Access Victoria University of Wellington

Description

<strong>Because of its wide range of applications, generative artificial intelligence (Generative AI) has received a lot of attention in academia and industry. Despite significant advances in computer vision and natural language processing, the use of Generative AI in tabular data is still underexplored. This gap is especially significant given the prevalence of tabular data as the primary data modality. This thesis seeks to close this gap by focusing on the efficient generation, evaluation, ...

Read more

Format

Research paper

Research format

Scholarly text / Thesis

Thesis level

Doctoral

Date created

2024

Creator

Alex Xing Wang

URL

https://figshare.com/articles/thesis/Data-Centric_AI_Tabular_Data_Synthesis_with_Deep_Generative_...

Related subjects

Modelling and simulation / Deep learning / Neural networks / Generative AI / Synthetic Data / Tabular Data / School: School of Mathematics and Statistics / Artificial intelligence / Applied computing / Degree Discipline: Statistics and Operations Research / Degree Discipline: Computer Science / Degree Level: Doctoral / Degree Name: Doctor of Philosophy / Degree Discipline: Data Science

What is the copyright status of this item?

Share

See below for specifics about how you may use this item.

More Information

Victoria University of Wellington has this to say about the rights status of this item:

CC BY-NC-ND 4.0

What can I do with this item?

You must always check with Victoria University of Wellington to confirm the specific terms of use, but this is our understanding:

Non-infringing use

NZ Copyright law does not prevent every use of a copyright work. You should consider what you can and cannot do with a copyright work.

Share it

This item is suitable for copying and sharing with others, without further permission.

No modifying

You are not allowed to adapt or remix this item into any other works.

No commercial use

You may not use this item commercially.