CapsLorentzNet: Integrating Physics Inspired Features with Graph Convolution

arXiv:2403.11826v1 Announce Type: cross
Abstract: With the advent of advanced machine learning techniques, boosted object tagging has witnessed significant progress. In this article, we take this field further by introducing novel architectural modifications compatible with a wide array of Graph Neural Network (GNN) architectures. Our approach advocates for integrating capsule layers, replacing the conventional decoding blocks in standard GNNs. These capsules are a group of neurons with vector activations. The orientation of these vectors represents important properties of the objects …

abstract advanced architectures array article arxiv capsule convolution cs.lg features gnn graph graph neural network hep-ex hep-ph machine machine learning machine learning techniques network neural network novel object physics progress tagging type