15 citations · 20 across the 10 of their papers we have counts for
6 papers · 1 filter
Generalized Graph Variational Autoencoders: Bounded Divergences Control Posterior Collapse
Kleyton da Costa, Bernardo Modenesi, Ivan F. M. Menezes +1
The variational graph autoencoder (VGAE) regularizes its posterior toward the prior with the Kullback-Leibler divergence, a choice inherited from the variational autoencoder rather…
Prompting is not enough: supervised baselines and leakage control for measuring shared decision-making with LLMs in pediatric encounters
Bernardo Modenesi, Jody Lin, Kimberly Kaphingst +4
Objectives: To determine whether zero-shot prompting of a large language model (LLM) is sufficient to detect shared decision-making (SDM) behaviors in real clinical encounters, and…
When Should Graph Attention Be Sparse? Learning a Per-Edge Tsallis Index
Kleyton da Costa, Bernardo Modenesi
Graph attention normalizes neighborhood scores with softmax, the maximum-entropy choice under Shannon statistics. But homophilic and heterophilic graphs want different attention sh…
Perspectives on Tsallis Statistics for Artificial Intelligence
Kleyton da Costa, Bernardo Modenesi
Tsallis statistics generalizes Boltzmann-Gibbs statistical mechanics through a single real parameter that controls the weight assigned to rare and frequent events. Originally p…
GraphNetz: Statistical Benchmarking of Graph Neural Networks with Paired Tests and Rank Aggregation
Kleyton da Costa, Bernardo Modenesi
Graph Neural Networks (GNNs) benchmarks often report single point estimates, even when performance differences are small relative to variation across random seeds, train/test split…
Divergence-Guided Particle Swarm Optimization
Kleyton da Costa, Bernardo Modenesi, Ivan F. M. Menezes +1
Particle Swarm Optimization (PSO) is susceptible to premature convergence when the swarm collapses around the global best, particularly on multimodal landscapes in higher dimension…