4 citations · 5 across the 4 of their papers we have counts for
6 papers
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…
Strange Non-Chaotic Attractors with Unpredictable Trajectories
Marat Akhmet, Mehmet Onur Fen, Astrit Tola
Continuous and discrete time systems possessing strange non-chaotic attractors are under investigation. It is demonstrated that unpredictable trajectories exist in the dynamics. A…
Unpredictable Strings
Marat Akhmet, Astrit Tola
A novel notion of unpredictable strings is revealed and utilized to define deterministic unpredictable sequences on a finite number of symbols. We prove the first law of large stri…
The Sequential Test for Chaos
Marat Akhmet, Mehmet Onur Fen, Astrit Tola
This paper reveals a novel numerical method, the sequential test, which approves chaos through sequences of numbers observations. The method alights alongside the Lyapunov exponent…