1 citations · 2 across the 16 of their papers we have counts for
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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…
The Financial Connectome: A Brain-Inspired Framework for Modeling Latent Market Dynamics
Yuda Bi, Vince D Calhoun
We propose the Financial Connectome, a new scientific discipline that models financial markets through the lens of brain functional architecture. Inspired by the foundational work…
MultiViT2: A Data-augmented Multimodal Neuroimaging Prediction Framework via Latent Diffusion Model
Bi Yuda, Jia Sihan, Gao Yutong +3
Multimodal medical imaging integrates diverse data types, such as structural and functional neuroimaging, to provide complementary insights that enhance deep learning predictions a…
GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis
Hu Xu, Yang Jingling, Jia Sihan +2
Generative models based on deep learning have shown significant potential in medical imaging, particularly for modality transformation and multimodal fusion in MRI-based brain imag…