Ciwan Ceylan

About Ciwan Ceylan

Ciwan Ceylan, With an exceptional h-index of 2 and a recent h-index of 2 (since 2020), a distinguished researcher at Kungliga Tekniska högskolan, specializes in the field of Node embeddings, Unsupervised learning, Anomaly Detection, Financial crime prevention.

His recent articles reflect a diverse array of research interests and contributions to the field:

Digraphwave: Scalable Extraction of Structural Node Embeddings via Diffusion on Directed Graphs

GraphDCA--a Framework for Node Distribution Comparison in Real and Synthetic Graphs

GraphDCA-a Framework for Node Distribution Comparison in Real and Synthetic Graphs

Learning Node Representations Using Stationary Flow Prediction on Large Payment and Cash Transaction Networks

Ciwan Ceylan Information

University

Position

PhD student at

Citations(all)

48

Citations(since 2020)

48

Cited By

19

hIndex(all)

2

hIndex(since 2020)

2

i10Index(all)

1

i10Index(since 2020)

1

Email

University Profile Page

Google Scholar

Ciwan Ceylan Skills & Research Interests

Node embeddings

Unsupervised learning

Anomaly Detection

Financial crime prevention

Top articles of Ciwan Ceylan

Digraphwave: Scalable Extraction of Structural Node Embeddings via Diffusion on Directed Graphs

arXiv preprint arXiv:2207.10149

2022/7/20

GraphDCA--a Framework for Node Distribution Comparison in Real and Synthetic Graphs

arXiv preprint arXiv:2202.03884

2022/2/8

GraphDCA-a Framework for Node Distribution Comparison in Real and Synthetic Graphs

2022

Learning Node Representations Using Stationary Flow Prediction on Large Payment and Cash Transaction Networks

2021/7/1

Ciwan Ceylan
Ciwan Ceylan

H-Index: 1

See List of Professors in Ciwan Ceylan University(Kungliga Tekniska högskolan)

Co-Authors

academic-engine