Target-Aware State-Adaptive p-Dirichlet Graph Neural Regression for Non-Invasive Body-Composition Estimation

arXiv:2608.29496 · cs.LG · Submitted 2026-08-30 · Read on arXiv

cs.LG

Submitted: 2026-08-30

Updated: 2026-08-30

Comments: 21 pages, 7 figures, 3 tables. The first four authors contribute equally to this work and are listed alphabetically. Corresponding authors: N. Drenska, Y. Wang and S. B. Heymsfield

Code: https://github.com/GowriPriyaSunkara/pLaplacianGraph-NN

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Graph Construction — 17× in this paper · explained in 3 episodes
• Latent Representation — 12× in this paper · explained in 2 episodes
• Appendicular Lean Mass — 11× in this paper
• Bone Mineral Density — 11× in this paper
• Clustering — 11× in this paper · explained in 2 episodes
• Benchmark — 10× in this paper · explained in 2 episodes
• Embeddings — 8× in this paper · explained in 2 episodes
• Gradient Flow — 8× in this paper · explained in 2 episodes
• Body Fat Percentage — 7× in this paper
• Semi-supervised Learning — 6× in this paper · explained in 4 episodes
• Regularization — 5× in this paper · explained in 3 episodes
• Root Mean Squared Error — 5× in this paper
• Accuracy — 4× in this paper · explained in 1 episode
• Pennington Biomedical Research Center — 4× in this paper
• Support Vector Regression — 3× in this paper
• Uniform Manifold Approximation and Projection — 3× in this paper
• Consistency — 2× in this paper · explained in 3 episodes
• Latent Representations — 2× in this paper · explained in 3 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Adjacency Matrix — 1× in this paper · explained in 1 episode
• External Validation — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• KL Regularization — 1× in this paper · explained in 2 episodes
• Least Squares Support Vector Regression — 1× in this paper
• Predictive Modeling — 1× in this paper · explained in 2 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Spectral clustering — 1× in this paper · explained in 2 episodes
• Variational Autoencoder (VAE) — 1× in this paper · explained in 3 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes

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