25 citations · 45 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 5 cited
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…
cs.LG2023★ 15 cited
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…
cs.LG2023★ 25 cited
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…