4 papers
SIEVE: Overcoming Topological Obstruction in Equivariant Self-Supervised Learning
Jongann Lee, Sun Woo Park, Yun Young Choi
We identify a theoretical incompatibility between 3D point cloud masked autoencoding and SE(3)-equivariant networks. We prove that standard masking triggers a topological collapse,…
A Functorial Formulation of Neighborhood Aggregating Deep Learning
Sun Woo Park, Yun Young Choi, U Jin Choi +1
We provide a mathematical interpretation of convolutional (or message passing) neural networks by using presheaves and copresheaves of the set of continuous functions over a topolo…
Topology-Informed Graph Transformer
Yun Young Choi, Sun Woo Park, Minho Lee +1
Transformers have revolutionized performance in Natural Language Processing and Vision, paving the way for their integration with Graph Neural Networks (GNNs). One key challenge in…
Enhancing Topological Dependencies in Spatio-Temporal Graphs with Cycle Message Passing Blocks
Minho Lee, Yun Young Choi, Sun Woo Park +3
Graph Neural Networks (GNNs) and Transformer-based models have been increasingly adopted to learn the complex vector representations of spatio-temporal graphs, capturing intricate…