4 papers
Second-Order Tensorial Partial Differential Equations on Graphs
Aref Einizade, Fragkiskos D. Malliaros, Jhony H. Giraldo
Processing data on multiple interacting graphs is crucial for many applications, but existing approaches rely mostly on discrete filtering or first-order continuous models, dampeni…
Subgraph Gaussian Embedding Contrast for Self-Supervised Graph Representation Learning
Shifeng Xie, Aref Einizade, Jhony H. Giraldo
Graph Representation Learning (GRL) is a fundamental task in machine learning, aiming to encode high-dimensional graph-structured data into low-dimensional vectors. Self-Supervised…
Continuous Simplicial Neural Networks
Aref Einizade, Dorina Thanou, Fragkiskos D. Malliaros +1
Simplicial complexes provide a powerful framework for modeling higher-order interactions in structured data, making them particularly suitable for applications such as trajectory p…
Higher-Order GNNs Meet Efficiency: Sparse Sobolev Graph Neural Networks
Jhony H. Giraldo, Aref Einizade, Andjela Todorovic +4
Graph Neural Networks (GNNs) have shown great promise in modeling relationships between nodes in a graph, but capturing higher-order relationships remains a challenge for large-sca…