8 citations · 9 across the 5 of their papers we have counts for
5 papers
Dynamic Linear Coregionalization for Realistic Synthetic Multivariate Time Series
Annita Vapsi, Penghang Liu, Saheed Obitayo +8
Synthetic data is essential for training foundation models for time series (FMTS), but most generators assume static correlations, and are typically missing realistic inter-channel…
Breaking Distortion-free Watermarks in Large Language Models
Shayleen Reynolds, Hengzhi He, Dung Daniel T. Ngo +5
In recent years, LLM watermarking has emerged as an attractive safeguard against AI-generated content, with promising applications in many real-world domains. However, there are gr…
Adaptive and Robust Watermark for Generative Tabular Data
Dung Daniel Ngo, Archan Ray, Akshay Seshadri +6
In recent years, watermarking generative tabular data has become a prominent framework to protect against the misuse of synthetic data. However, while most prior work in watermarki…
Synthetic Data Applications in Finance
Vamsi K. Potluru, Daniel Borrajo, Andrea Coletta +17
Synthetic data has made tremendous strides in various commercial settings including finance, healthcare, and virtual reality. We present a broad overview of prototypical applicatio…
A supervised generative optimization approach for tabular data
Shinpei Nakamura-Sakai, Fadi Hamad, Saheed Obitayo +1
Synthetic data generation has emerged as a crucial topic for financial institutions, driven by multiple factors, such as privacy protection and data augmentation. Many algorithms h…