Spectra defines and controls effective capacity in graph embeddings via the Shannon effective rank of a trace-normalized kernel spectrum, making capacity a post-fit property rather than a pre-training hyperparameter.
Hm-ldm: A hybrid-membership latent distance model
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.LG 2years
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UNVERDICTED 2representative citing papers
Graph nodes are embedded as simplex compositions via ILR coordinates to yield intrinsically interpretable representations that preserve Aitchison geometry and enable subcompositional analysis.
citing papers explorer
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Rank Is Not Capacity: Spectral Occupancy for Latent Graph Models
Spectra defines and controls effective capacity in graph embeddings via the Shannon effective rank of a trace-normalized kernel spectrum, making capacity a post-fit property rather than a pre-training hyperparameter.
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Aitchison Embeddings for Learning Compositional Graph Representations
Graph nodes are embedded as simplex compositions via ILR coordinates to yield intrinsically interpretable representations that preserve Aitchison geometry and enable subcompositional analysis.