Zobrazeno 1 - 10
of 119
pro vyhledávání: '"Coskunuzer, Baris"'
Publikováno v:
MICCAI TGI3 2024
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 the expertise of experienced pathologists. Recent advances in deep learn
Externí odkaz:
http://arxiv.org/abs/2410.09818
Graph embeddings play a critical role in graph representation learning, allowing machine learning models to explore and interpret graph-structured data. However, existing methods often rely on opaque, high-dimensional embeddings, limiting interpretab
Externí odkaz:
http://arxiv.org/abs/2410.01778
Graph Neural Networks (GNNs) have revolutionized the domain of graph representation learning by utilizing neighborhood aggregation schemes in many popular architectures, such as message passing graph neural networks (MPGNNs). This scheme involves ite
Externí odkaz:
http://arxiv.org/abs/2410.02158
Over the past decade, Graph Neural Networks (GNNs) have transformed graph representation learning. In the widely adopted message-passing GNN framework, nodes refine their representations by aggregating information from neighboring nodes iteratively.
Externí odkaz:
http://arxiv.org/abs/2410.01802
Topological Machine Learning (TML) is an emerging field that leverages techniques from algebraic topology to analyze complex data structures in ways that traditional machine learning methods may not capture. This tutorial provides a comprehensive int
Externí odkaz:
http://arxiv.org/abs/2409.02901
Autor:
Shirzadkhani, Razieh, Ngo, Tran Gia Bao, Shamsi, Kiarash, Huang, Shenyang, Poursafaei, Farimah, Azad, Poupak, Rabbany, Reihaneh, Coskunuzer, Baris, Rabusseau, Guillaume, Akcora, Cuneyt Gurcan
The field of temporal graph learning aims to learn from evolving network data to forecast future interactions. Given a collection of observed temporal graphs, is it possible to predict the evolution of an unseen network from the same domain? To answe
Externí odkaz:
http://arxiv.org/abs/2406.10426
In this paper, we bring a new perspective to persistent homology by incorporating key concepts from metric geometry. For a given compact subset $X$ of a Banach space $Y$, we study the topological features appearing in family $N_\bullet(X\subset Y)$ o
Externí odkaz:
http://arxiv.org/abs/2403.13980
Publikováno v:
AAAI 2024
Learning time-evolving objects such as multivariate time series and dynamic networks requires the development of novel knowledge representation mechanisms and neural network architectures, which allow for capturing implicit time-dependent information
Externí odkaz:
http://arxiv.org/abs/2401.13157
Autor:
Segovia-Dominguez, Ignacio, Chen, Yuzhou, Akcora, Cuneyt G., Zhen, Zhiwei, Kantarcioglu, Murat, Gel, Yulia R., Coskunuzer, Baris
Publikováno v:
LoG 2023
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 technique within TDA is persistent homology (PH), which furnishes an exclusive
Externí odkaz:
http://arxiv.org/abs/2401.13713
The rise of cryptocurrencies like Bitcoin, which enable transactions with a degree of pseudonymity, has led to a surge in various illicit activities, including ransomware payments and transactions on darknet markets. These illegal activities often ut
Externí odkaz:
http://arxiv.org/abs/2306.07974