5 papers
SpeedCP: Fast Kernel-based Conditional Conformal Prediction
Yating Liu, Yeo Jin Jung, Zixuan Wu +2
Conformal prediction provides distribution-free prediction sets with finite-sample conditional guarantees. We build upon the RKHS-based framework of Gibbs et al. (2023), which leve…
Jigsaw Regularization in Whole-Slide Image Classification
So Won Jeong, Veronika RoÄková
Computational pathology involves the digitization of stained tissues into whole-slide images (WSIs) that contain billions of pixels arranged as contiguous patches. Statistical anal…
Filtering with Confidence: When Data Augmentation Meets Conformal Prediction
Zixuan Wu, So Won Jeong, Yating Liu +2
With promising empirical performance across a wide range of applications, synthetic data augmentation appears a viable solution to data scarcity and the demands of increasingly dat…
LOBSTUR: A Local Bootstrap Framework for Tuning Unsupervised Representations in Graph Neural Networks
So Won Jeong, Claire Donnat
Graph Neural Networks (GNNs) are increasingly used in conjunction with unsupervised learning techniques to learn powerful node representations, but their deployment is hindered by…
GNUMAP: A Parameter-Free Approach to Unsupervised Dimensionality Reduction via Graph Neural Networks
Jihee You, So Won Jeong, Claire Donnat
With the proliferation of Graph Neural Network (GNN) methods stemming from contrastive learning, unsupervised node representation learning for graph data is rapidly gaining tractio…