4 citations · 5 across the 4 of their papers we have counts for
5 papers
Test-time Fourier Style Calibration for Domain Generalization
Xingchen Zhao, Chang Liu, Anthony Sicilia +2
The topic of generalizing machine learning models learned on a collection of source domains to unknown target domains is challenging. While many domain generalization (DG) methods…
PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging
Anthony Sicilia, Xingchen Zhao, Anastasia Sosnovskikh +1
Application of deep neural networks to medical imaging tasks has in some sense become commonplace. Still, a "thorn in the side" of the deep learning movement is the argument that d…
Multi-Domain Learning by Meta-Learning: Taking Optimal Steps in Multi-Domain Loss Landscapes by Inner-Loop Learning
Anthony Sicilia, Xingchen Zhao, Davneet Minhas +5
We consider a model-agnostic solution to the problem of Multi-Domain Learning (MDL) for multi-modal applications. Many existing MDL techniques are model-dependent solutions which e…
Robust White Matter Hyperintensity Segmentation on Unseen Domain
Xingchen Zhao, Anthony Sicilia, Davneet Minhas +5
Typical machine learning frameworks heavily rely on an underlying assumption that training and test data follow the same distribution. In medical imaging which increasingly begun a…
Learning by Ignoring, with Application to Domain Adaptation
Xingchen Zhao, Xuehai He, Pengtao Xie
Learning by ignoring, which identifies less important things and excludes them from the learning process, is broadly practiced in human learning and has shown ubiquitous effectiven…