127 citations · 523 across the 58 of their papers we have counts for
7 papers · 1 filter
FedNI: Federated Graph Learning with Network Inpainting for Population-Based Disease Prediction
Liang Peng, Nan Wang, Nicha Dvornek +2
Graph Convolutional Neural Networks (GCNs) are widely used for graph analysis. Specifically, in medical applications, GCNs can be used for disease prediction on a population graph,…
DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization
Boyue Li, Zhize Li, Yuejie Chi
Emerging applications in multi-agent environments such as internet-of-things, networked sensing, autonomous systems and federated learning, call for decentralized algorithms for fi…
A Metamodel Structure For Regression Analysis: Application To Prediction Of Autism Spectrum Disorder Severity
Shiyu Wang, Nicha C. Dvornek
Traditional regression models do not generalize well when learning from small and noisy datasets. Here we propose a novel metamodel structure to improve the regression result. The…
Estimating Reproducible Functional Networks Associated with Task Dynamics using Unsupervised LSTMs
Nicha C. Dvornek, Pamela Ventola, James S. Duncan
We propose a method for estimating more reproducible functional networks that are more strongly associated with dynamic task activity by using recurrent neural networks with long s…
Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity
Nicha C. Dvornek, Xiaoxiao Li, Juntang Zhuang +2
Heterogeneous presentation of a neurological disorder suggests potential differences in the underlying pathophysiological changes that occur in the brain. We propose to model heter…
MALI: A memory efficient and reverse accurate integrator for Neural ODEs
Juntang Zhuang, Nicha C. Dvornek, Sekhar Tatikonda +1
Neural ordinary differential equations (Neural ODEs) are a new family of deep-learning models with continuous depth. However, the numerical estimation of the gradient in the contin…