1 citations · 1 across the 4 of their papers we have counts for
4 papers
Representation learning in multiplex graphs: Where and how to fuse information?
Piotr Bielak, Tomasz Kajdanowicz
In recent years, unsupervised and self-supervised graph representation learning has gained popularity in the research community. However, most proposed methods are focused on homog…
Unveiling the Potential of Probabilistic Embeddings in Self-Supervised Learning
Denis Janiak, Jakub Binkowski, Piotr Bielak +1
In recent years, self-supervised learning has played a pivotal role in advancing machine learning by allowing models to acquire meaningful representations from unlabeled data. An i…
Graph-level representations using ensemble-based readout functions
Jakub Binkowski, Albert Sawczyn, Denis Janiak +2
Graph machine learning models have been successfully deployed in a variety of application areas. One of the most prominent types of models - Graph Neural Networks (GNNs) - provides…
RAFEN -- Regularized Alignment Framework for Embeddings of Nodes
Kamil Tagowski, Piotr Bielak, Jakub Binkowski +1
Learning representations of nodes has been a crucial area of the graph machine learning research area. A well-defined node embedding model should reflect both node features and the…