12 citations · 109 across the 50 of their papers we have counts for
9 papers · 1 filter
TopOC: Topological Deep Learning for Ovarian and Breast Cancer Diagnosis
Saba Fatema, Brighton Nuwagira, Sayoni Chakraborty +2
Microscopic examination of slides prepared from tissue samples is the primary tool for detecting and classifying cancerous lesions, a process that is time-consuming and requires th…
PROXI: Challenging the GNNs for Link Prediction
Astrit Tola, Jack Myrick, Baris Coskunuzer
Over the past decade, Graph Neural Networks (GNNs) have transformed graph representation learning. In the widely adopted message-passing GNN framework, nodes refine their represent…
SCNode: Spatial and Contextual Coordinates for Graph Representation Learning
Md Joshem Uddin, Astrit Tola, Varin Sikand +2
Effective node representation lies at the heart of Graph Neural Networks (GNNs), as it directly impacts their ability to perform downstream tasks such as node classification and li…
TopER: Topological Embeddings in Graph Representation Learning
Astrit Tola, Funmilola Mary Taiwo, Cuneyt Gurcan Akcora +1
Graph embeddings play a critical role in graph representation learning, allowing machine learning models to explore and interpret graph-structured data. However, existing methods o…
Topological Methods in Machine Learning: A Tutorial for Practitioners
Baris Coskunuzer, Cüneyt Gürcan Akçora
Topological Machine Learning (TML) is an emerging field that leverages techniques from algebraic topology to analyze complex data structures in ways that traditional machine learni…
MiNT: Multi-Network Training for Transfer Learning on Temporal Graphs
Kiarash Shamsi, Tran Gia Bao Ngo, Razieh Shirzadkhani +7
Temporal Graph Learning (TGL) has become a robust framework for discovering patterns in dynamic networks and predicting future interactions. While existing research has largely con…