6 citations · 13 across the 7 of their papers we have counts for
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cs.LG2024
Mind the truncation gap: challenges of learning on dynamic graphs with recurrent architectures
João Bravo, Jacopo Bono, Pedro Saleiro +2
Systems characterized by evolving interactions, prevalent in social, financial, and biological domains, are effectively modeled as continuous-time dynamic graphs (CTDGs). To manage…
cs.LG2024
NRGBoost: Energy-Based Generative Boosted Trees
João Bravo
Despite the rise to dominance of deep learning in unstructured data domains, tree-based methods such as Random Forests (RF) and Gradient Boosted Decision Trees (GBDT) are still the…
cs.LG2024
RIFF: Inducing Rules for Fraud Detection from Decision Trees
João Lucas Martins, João Bravo, Ana Sofia Gomes +2
Financial fraud is the cause of multi-billion dollar losses annually. Traditionally, fraud detection systems rely on rules due to their transparency and interpretability, key featu…