29 citations · 40 across the 28 of their papers we have counts for
8 papers · 1 filter
Latent graph encoding of multimodal neuroimaging features with generative AI architectures
Ishaan Batta, Meenu Ajith, Vince Calhoun
While generative models enable encoding of complex neuroimaging data for feature generation and reconstruction, developing optimal architectural frameworks with appropriate encodin…
A 1/R Law for Kurtosis Contrast in Balanced Mixtures
Yuda Bi, Wenjun Xiao, Linhao Bai +1
Kurtosis-based Independent Component Analysis (ICA) weakens in wide, balanced mixtures. We prove a sharp redundancy law: for a standardized projection with effective width $R_{\mat…
Redundancy as a Structural Information Principle for Learning and Generalization
Yuda Bi, Ying Zhu, Vince D Calhoun
We present a theoretical framework that extends classical information theory to finite and structured systems by redefining redundancy as a fundamental property of information orga…
Scaling Laws are Redundancy Laws
Yuda Bi, Vince D Calhoun
Scaling laws, a defining feature of deep learning, reveal a striking power-law improvement in model performance with increasing dataset and model size. Yet, their mathematical orig…
A Privacy-Preserving Domain Adversarial Federated learning for multi-site brain functional connectivity analysis
Yipu Zhang, Likai Wang, Kuan-Jui Su +7
Resting-state functional magnetic resonance imaging (rs-fMRI) and its derived functional connectivity networks (FCNs) have become critical for understanding neurological disorders.…
Hierarchical Spatio-Temporal State-Space Modeling for fMRI Analysis
Yuxiang Wei, Anees Abrol, Vince Calhoun
Recent advances in deep learning structured state space models, especially the Mamba architecture, have demonstrated remarkable performance improvements while maintaining linear co…
Spectral Introspection Identifies Group Training Dynamics in Deep Neural Networks for Neuroimaging
Bradley T. Baker, Vince D. Calhoun, Sergey M. Plis
Neural networks, whice have had a profound effect on how researchers study complex phenomena, do so through a complex, nonlinear mathematical structure which can be difficult for h…
An AO-ADMM approach to constraining PARAFAC2 on all modes
Marie Roald, Carla Schenker, Vince D. Calhoun +4
Analyzing multi-way measurements with variations across one mode of the dataset is a challenge in various fields including data mining, neuroscience and chemometrics. For example,…