publications

2023

  1. A Hierarchical Block Distance Model for Ultra Low-Dimensional Graph Representations
    Nikolaos Nakis, Abdulkadir Çelikkanat, Sune Lehmann Jørgensen, and 1 more author
    In , Aug 2023
    DOI arXiv Code (Accepted)
  2. Characterizing Polarization in Social Networks using the Signed Relational Latent Distance Model
    Nikolaos Nakis, Abdulkadir Çelikkanat, Louis Boucherie, and 5 more authors
    In International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
    arXiv Code (Accepted)
  3. HM-LDM: A Hybrid-Membership Latent Distance Model
    Nikolaos Nakis, Abdulkadir Çelikkanat, and Morten Mørup
    In Complex Networks and Their Applications XI, 2023
    DOI arXiv Code Slides (Oral Presentation)

2022

  1. Piecewise-Velocity Model for Learning Continuous-time Dynamic Node Representations
    Abdulkadir Çelikkanat, Nikolaos Nakis, and Morten Mørup
    In Proceedings of the First Learning on Graphs Conference, Dec 2022
    Link arXiv Code Poster Project Website
  2. NodeSig: Binary Node Embeddings via Random Walk Diffusion
    Abdulkadir Çelikkanat, Apostolos N. Papadopoulos, and Fragkiskos D. Malliaros
    In International Conference on Advances in Social Networks Analysis and Mining, Dec 2022
    arXiv Code Slides Project Website (Oral Presentation)
  3. BraneMF: Integration of biological networks for functional analysis of proteins
    Surabhi Jagtap, Abdulkadir Çelikkanat, Aurélie Pirayre, and 3 more authors
    Bioinformatics, Nov 2022
    DOI Code
  4. Multiple Kernel Representation Learning on Networks
    Abdulkadir Çelikkanat, Yanning Shen, and Fragkiskos Malliaros
    IEEE Transactions on Knowledge and Data Engineering, Nov 2022
    DOI arXiv Code Project Website

2021

  1. Multiomics Data Integration for Gene Regulatory Network Inference with Exponential Family Embeddings
    Surabhi Jagtap, Abdulkadir Çelikkanat, Aurelic Piravre, and 3 more authors
    In European Signal Processing Conference (EUSIPCO), Nov 2021
    DOI Code
  2. Graph Representation Learning with Random Walk Diffusions
    Abdulkadir Çelikkanat
    Ph.D. Thesis, CentraleSupélec, Université Paris-Saclay, Apr 2021
    Link PDF Slides
  3. Topic-aware latent models for representation learning on networks
    Abdulkadir Çelikkanat, and Fragkiskos D. Malliaros
    Pattern Recognition Letters, Apr 2021
    DOI arXiv Code Project Website

2020

  1. Exponential Family Graph Embeddings
    Abdulkadir Çelikkanat, and Fragkiskos D. Malliaros
    Proceedings of the AAAI Conference on Artificial Intelligence, Apr 2020
    DOI arXiv Code Project Website

2019

  1. Learning Node Embeddings with Exponential Family Distributions
    Abdulkadir Çelikkanat, and Fragkiskos Malliaros
    In Neural Information Processing Systems - Workshop on Graph Representation Learning, Dec 2019
    Link PDF Code Project Website
  2. Kernel Node Embeddings
    Abdulkadir Çelikkanat, and Fragkiskos D. Malliaros
    In IEEE Global Conference on Signal and Information Processing (GlobalSIP), Dec 2019
    DOI arXiv Code Project Website

2018

  1. TNE: A Latent Model for Representation Learning on Networks
    Abdulkadir Çelikkanat, and Fragkiskos D. Malliaros
    In Neural Information Processing Systems - Relational Representation Learning Workshop (NeurIPS-R2L), Dec 2018
    Link PDF Code Poster Project Website

2017

  1. Sampling methods for random simple and bipartite graphs with prescribed degree sequences
    Abdulkadir Çelikkanat
    Master’s Thesis, Fen Bilimleri Enstitüsü, Bogaziçi University, Dec 2017
    Link PDF Code Presentation