1 citations · 1 across the 5 of their papers we have counts for
5 papers
TopoGCL: Topological Graph Contrastive Learning
Yuzhou Chen, Jose Frias, Yulia R. Gel
Graph contrastive learning (GCL) has recently emerged as a new concept which allows for capitalizing on the strengths of graph neural networks (GNNs) to learn rich representations…
EMP: Effective Multidimensional Persistence for Graph Representation Learning
Ignacio Segovia-Dominguez, Yuzhou Chen, Cuneyt G. Akcora +4
Topological data analysis (TDA) is gaining prominence across a wide spectrum of machine learning tasks that spans from manifold learning to graph classification. A pivotal techniqu…
Time-Aware Knowledge Representations of Dynamic Objects with Multidimensional Persistence
Baris Coskunuzer, Ignacio Segovia-Dominguez, Yuzhou Chen +1
Learning time-evolving objects such as multivariate time series and dynamic networks requires the development of novel knowledge representation mechanisms and neural network archit…
Topological Pooling on Graphs
Yuzhou Chen, Yulia R. Gel
Graph neural networks (GNNs) have demonstrated a significant success in various graph learning tasks, from graph classification to anomaly detection. There recently has emerged a n…
Seven open problems in applied combinatorics
Sinan G. Aksoy, Ryan Bennink, Yuzhou Chen +10
We present and discuss seven different open problems in applied combinatorics. The application areas relevant to this compilation include quantum computing, algorithmic differentia…