7 citations · 11 across the 7 of their papers we have counts for
Showing 2025Show all
3 papers · 1 filter
cs.LG2025
Beyond the Laplacian: Interpolated Spectral Augmentation for Graph Neural Networks
Ziyao Cui, Edric Tam
Graph neural networks (GNNs) are fundamental tools in graph machine learning. The performance of GNNs relies crucially on the availability of informative node features, which can b…
stat.ML2025★ 3 cited
On the Statistical Capacity of Deep Generative Models
Edric Tam, David B. Dunson
Deep generative models are routinely used in generating samples from complex, high-dimensional distributions. Despite their apparent successes, their statistical properties are not…
stat.ML2025
Assessing the Distributional Fidelity of Synthetic Chest X-rays using the Embedded Characteristic Score
Edric Tam, Barbara E Engelhardt
Chest X-ray (CXR) images are among the most commonly used diagnostic imaging modalities in clinical practice. Stringent privacy constraints often limit the public dissemination of…