25 citations · 90 across the 12 of their papers we have counts for
7 papers · 1 filter
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes
Nabeel Seedat, Nicolas Huynh, Boris van Breugel +1
Machine Learning (ML) in low-data settings remains an underappreciated yet crucial problem. Hence, data augmentation methods to increase the sample size of datasets needed for ML a…
Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data
Boris van Breugel, Nabeel Seedat, Fergus Imrie +1
Evaluating the performance of machine learning models on diverse and underrepresented subgroups is essential for ensuring fairness and reliability in real-world applications. Howev…
Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models
Yangming Li, Boris van Breugel, Mihaela van der Schaar
Because diffusion models have shown impressive performances in a number of tasks, such as image synthesis, there is a trend in recent works to prove (with certain assumptions) that…
The Spherical Grasshopper Problem
Boris van Breugel
The aim of this essay is to better understand the Grasshopper Problem on the surface of the unit sphere. The problem is motivated by analysing Bell inequalities, but can be formula…
Synthetic data, real errors: how (not) to publish and use synthetic data
Boris van Breugel, Zhaozhi Qian, Mihaela van der Schaar
Generating synthetic data through generative models is gaining interest in the ML community and beyond, promising a future where datasets can be tailored to individual needs. Unfor…
Beyond Privacy: Navigating the Opportunities and Challenges of Synthetic Data
Boris van Breugel, Mihaela van der Schaar
Generating synthetic data through generative models is gaining interest in the ML community and beyond. In the past, synthetic data was often regarded as a means to private data re…
Membership Inference Attacks against Synthetic Data through Overfitting Detection
Boris van Breugel, Hao Sun, Zhaozhi Qian +1
Data is the foundation of most science. Unfortunately, sharing data can be obstructed by the risk of violating data privacy, impeding research in fields like healthcare. Synthetic…