2 Papers at IJCNN'21

Two papers accepted at IJCNN 2021! The first, “Modeling Edge Features with Deep Graph Bayesian Networks”, extends the Contextual Graph Markov Model to the processing of arbitrary edge features! The second, “Concept Matching for Low-resource Classification”, presents a new way to train prototypes of important words to perform classification when supervised data is limited. You can find the papers on my publication list! Congrats to all my co-authors!

Federico Errica
Federico Errica
PhD in Computer Science