2 papers
cs.AI2024
Answer Set Networks: Casting Answer Set Programming into Deep Learning
Arseny Skryagin, Daniel Ochs, Phillip Deibert +3
Although Answer Set Programming (ASP) allows constraining neural-symbolic (NeSy) systems, its employment is hindered by the prohibitive costs of computing stable models and the CPU…
cs.LG2024
Graph Neural Networks Need Cluster-Normalize-Activate Modules
Arseny Skryagin, Felix Divo, Mohammad Amin Ali +2
Graph Neural Networks (GNNs) are non-Euclidean deep learning models for graph-structured data. Despite their successful and diverse applications, oversmoothing prohibits deep archi…