2 citations · 2 across the 3 of their papers we have counts for
3 papers
Do Deep Ensembles Actually Capture Uncertainty in Graph Neural Networks?
Pedro C. Vieira, Pedro Ribeiro, Viacheslav Borovitskiy
While deep ensembles are widely considered to be the default method for uncertainty quantification in deep learning, their effectiveness for graph-structured data is often simply a…
Studying and Improving Graph Neural Network-based Motif Estimation
Pedro C. Vieira, Miguel E. P. Silva, Pedro Manuel Pinto Ribeiro
Graph Neural Networks (GNNs) are a predominant method for graph representation learning. However, beyond subgraph frequency estimation, their application to network motif significa…
S+t-SNE -- Bringing Dimensionality Reduction to Data Streams
Pedro C. Vieira, João P. Montrezol, João T. Vieira +1
We present S+t-SNE, an adaptation of the t-SNE algorithm designed to handle infinite data streams. The core idea behind S+t-SNE is to update the t-SNE embedding incrementally as ne…