iLoRA is the first Bayesian graph-conditioned LoRA framework that infers latent interaction graphs to generate input-dependent low-rank updates, jointly learning predictions and structure for microbiome diagnosis.
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A systematic perturbative expansion around the neutral solution yields fixation probabilities for multi-allele Moran processes under weak selection.
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iLoRA: Bayesian Low-Rank Adaptation with Latent Interaction Graphs for Microbiome Diagnosis
iLoRA is the first Bayesian graph-conditioned LoRA framework that infers latent interaction graphs to generate input-dependent low-rank updates, jointly learning predictions and structure for microbiome diagnosis.
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Fixation probabilities for multi-allele Moran dynamics with weak selection
A systematic perturbative expansion around the neutral solution yields fixation probabilities for multi-allele Moran processes under weak selection.