activity
20192026
most citedCNN-TFT explained by SHAP with multi-head attention weights for time series forecasting

1 citations · 2 across the 8 of their papers we have counts for

collaborators
Showing 2025Show all

2 papers · 1 filter

cs.LG2025★ 1 cited

CNN-TFT explained by SHAP with multi-head attention weights for time series forecasting

Stefano F. Stefenon, João P. Matos-Carvalho, Valderi R. Q. Leithardt +1

Convolutional neural networks (CNNs) and transformer architectures offer strengths for modeling temporal data: CNNs excel at capturing local patterns and translational invariances,…

cs.LG2025

Time series forecasting based on optimized LLM for fault prediction in distribution power grid insulators

João Pedro Matos-Carvalho, Stefano Frizzo Stefenon, Valderi Reis Quietinho Leithardt +1

Surface contamination on electrical grid insulators leads to an increase in leakage current until an electrical discharge occurs, which can result in a power system shutdown. To mi…