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08/19/2023
PDL: Regularizing Multiple Instance Learning with Progressive Dropout Layers
Multiple instance learning (MIL) was a weakly supervised learning approa...
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06/02/2023
NNMobile-Net: Rethinking CNN Design for Deep Learning-Based Retinopathy Research
Retinal diseases (RD) are the leading cause of severe vision loss or bli...
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05/30/2023
SFCNeXt: a simple fully convolutional network for effective brain age estimation with small sample size
Deep neural networks (DNN) have been designed to predict the chronologic...
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03/31/2023
A Surface-Based Federated Chow Test Model for Integrating APOE Status, Tau Deposition Measure, and Hippocampal Surface Morphometry
Background: Alzheimer's Disease (AD) is the most common type of age-rela...
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02/08/2023
TetCNN: Convolutional Neural Networks on Tetrahedral Meshes
Convolutional neural networks (CNN) have been broadly studied on images,...
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02/06/2023
OTRE: Where Optimal Transport Guided Unpaired Image-to-Image Translation Meets Regularization by Enhancing
Non-mydriatic retinal color fundus photography (CFP) is widely available...
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02/06/2023
Optimal Transport Guided Unsupervised Learning for Enhancing low-quality Retinal Images
Real-world non-mydriatic retinal fundus photography is prone to artifact...
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10/17/2022
Anisotropic Multi-Scale Graph Convolutional Network for Dense Shape Correspondence
This paper studies 3D dense shape correspondence, a key shape analysis a...
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10/12/2022
Self-Supervised Equivariant Regularization Reconciles Multiple Instance Learning: Joint Referable Diabetic Retinopathy Classification and Lesion Segmentation
Lesion appearance is a crucial clue for medical providers to distinguish...
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07/20/2022
Matrix Kendall's tau in High-dimensions: A Robust Statistic for Matrix Factor Model
In this article, we first propose generalized row/column matrix Kendall'...
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05/10/2022
OTFPF: Optimal Transport-Based Feature Pyramid Fusion Network for Brain Age Estimation with 3D Overlapped ConvNeXt
Chronological age of healthy brain is able to be predicted using deep ne...
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04/29/2022
Distributed Learning for Principle Eigenspaces without Moment Constraints
Distributed Principal Component Analysis (PCA) has been studied to deal ...
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12/31/2021
Channel Estimation for Hybrid Massive MIMO Systems with Adaptive-Resolution ADCs
Achieving high channel estimation accuracy and reducing hardware cost as...
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10/30/2021
Geometry-Aware Hierarchical Bayesian Learning on Manifolds
Bayesian learning with Gaussian processes demonstrates encouraging regre...
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10/20/2021
Predicting Tau Accumulation in Cerebral Cortex with Multivariate MRI Morphometry Measurements, Sparse Coding, and Correntropy
Biomarker-assisted diagnosis and intervention in Alzheimer's disease (AD...
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04/01/2021
Cortical Morphometry Analysis based on Worst Transportation Theory
Biomarkers play an important role in early detection and intervention in...
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07/19/2020
Deep Representation Learning For Multimodal Brain Networks
Applying network science approaches to investigate the functions and ana...
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05/25/2020
Optimizing Visual Cortex Parameterization with Error-Tolerant Teichmuller Map in Retinotopic Mapping
The mapping between the visual input on the retina to the cortical surfa...
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02/24/2020
Variational Wasserstein Barycenters for Geometric Clustering
We propose to compute Wasserstein barycenters (WBs) by solving for Monge...
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02/09/2020
The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up
We present the findings of "The Alzheimer's Disease Prediction Of Longit...
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03/20/2019
Regularize, Expand and Compress: Multi-task based Lifelong Learning via NonExpansive AutoML
Lifelong learning, the problem of continual learning where tasks arrive ...
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03/06/2019
Graph Neural Networks for User Identity Linkage
The increasing popularity and diversity of social media sites has encour...
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02/03/2019
MICIK: MIning Cross-Layer Inherent Similarity Knowledge for Deep Model Compression
State-of-the-art deep model compression methods exploit the low-rank app...
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12/02/2018
Regularized Wasserstein Means Based on Variational Transportation
We raise the problem of regularizing Wasserstein means and propose sever...
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09/08/2018
Brain Morphometry Analysis with Surface Foliation Theory
Brain morphometry study plays a fundamental role in neuroimaging researc...
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06/23/2018
Variational Wasserstein Clustering
We propose a new clustering method based on optimal transportation. We s...
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06/04/2018
Dynamically Hierarchy Revolution: DirNet for Compressing Recurrent Neural Network on Mobile Devices
Recurrent neural networks (RNNs) achieve cutting-edge performance on a v...
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04/27/2017
Large-scale Feature Selection of Risk Genetic Factors for Alzheimer's Disease via Distributed Group Lasso Regression
Genome-wide association studies (GWAS) have achieved great success in th...
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08/19/2016
