1 citations · 1 across the 3 of their papers we have counts for
3 papers
Embarrassingly Parallel GFlowNets
Tiago da Silva, Luiz Max Carvalho, Amauri Souza +2
GFlowNets are a promising alternative to MCMC sampling for discrete compositional random variables. Training GFlowNets requires repeated evaluations of the unnormalized target dist…
In-n-Out: Calibrating Graph Neural Networks for Link Prediction
Erik Nascimento, Diego Mesquita, Samuel Kaski +1
Deep neural networks are notoriously miscalibrated, i.e., their outputs do not reflect the true probability of the event we aim to predict. While networks for tabular or image data…
Going beyond persistent homology using persistent homology
Johanna Immonen, Amauri H. Souza, Vikas Garg
Representational limits of message-passing graph neural networks (MP-GNNs), e.g., in terms of the Weisfeiler-Leman (WL) test for isomorphism, are well understood. Augmenting these…