research
∙
03/02/2023
Evidence-empowered Transfer Learning for Alzheimer's Disease
Transfer learning has been widely utilized to mitigate the data scarcity...
share
research
∙
05/13/2022
Test-time Fourier Style Calibration for Domain Generalization
The topic of generalizing machine learning models learned on a collectio...
research
∙
10/11/2021
Point Cloud Augmentation with Weighted Local Transformations
Despite the extensive usage of point clouds in 3D vision, relatively lim...
research
∙
04/12/2021
PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging
Application of deep neural networks to medical imaging tasks has in some...
research
∙
02/25/2021
Multi-Domain Learning by Meta-Learning: Taking Optimal Steps in Multi-Domain Loss Landscapes by Inner-Loop Learning
We consider a model-agnostic solution to the problem of Multi-Domain Lea...
research
∙
02/12/2021
Robust White Matter Hyperintensity Segmentation on Unseen Domain
Typical machine learning frameworks heavily rely on an underlying assump...
research
∙
02/07/2021
Domain Adversarial Neural Networks for Domain Generalization: When It Works and How to Improve
Theoretically, domain adaptation is a well-researched problem. Further, ...
research
∙
11/24/2018
Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples with Applications to Neuroimaging
Generative models using neural network have opened a door to large-scale...
research
∙
04/19/2018
