9 citations · 11 across the 3 of their papers we have counts for
5 papers
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,…
GPT-4.1 Sets the Standard in Automated Experiment Design Using Novel Python Libraries
Nuno Fachada, Daniel Fernandes, Carlos M. Fernandes +2
Large Language Models (LLMs) have advanced rapidly as tools for automating code generation in scientific research, yet their ability to interpret and use unfamiliar Python APIs for…
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…
DeepSeek-V3, GPT-4, Phi-4, and LLaMA-3.3 generate correct code for LoRaWAN-related engineering tasks
Daniel Fernandes, João P. Matos-Carvalho, Carlos M. Fernandes +1
This paper investigates the performance of 16 Large Language Models (LLMs) in automating LoRaWAN-related engineering tasks involving optimal placement of drones and received power…
QiBERT -- Classifying Online Conversations Messages with BERT as a Feature
Bruno D. Ferreira-Saraiva, Zuil Pirola, João P. Matos-Carvalho +1
Recent developments in online communication and their usage in everyday life have caused an explosion in the amount of a new genre of text data, short text. Thus, the need to class…