Julian Busch

According to our database, Julian Busch authored at least 10 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification.

Sandra Gilhuber, Julian Busch, Daniel Rotthues, Christian M. M. Frey, Thomas Seidl

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

2021

Representation learning on complex data.

Julian Busch

PhD thesis, 2021

NF-GNN: Network Flow Graph Neural Networks for Malware Detection and Classification.

Julian Busch, Anton Kocheturov, Volker Tresp, Thomas Seidl

Proceedings of the SSDBM 2021: 33rd International Conference on Scientific and Statistical Database Management, 2021

Implicit Hough Transform Neural Networks for Subspace Clustering.

Julian Busch, Maximilian Hünemörder, Janis Held, Peer Kröger, Thomas Seidl

Proceedings of the 2021 International Conference on Data Mining, 2021

2020

Learning Self-Expression Metrics for Scalable and Inductive Subspace Clustering.

Julian Busch, Evgeniy Faerman, Matthias Schubert, Thomas Seidl

CoRR, 2020

Ada-LLD: Adaptive Node Similarity Using Multi-Scale Local Label Distributions.

Evgeniy Faerman, Felix Borutta, Julian Busch, Matthias Schubert

Proceedings of the IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2020

Grace - Limiting the Number of Grid Cells for Clustering High-Dimensional Data.

Anna Beer, Daniyal Kazempour, Julian Busch, Alexander Tekles, Thomas Seidl

Proceedings of the Conference "Lernen, 2020

PushNet: Efficient and Adaptive Neural Message Passing.

Julian Busch, Jiaxing Pi, Thomas Seidl

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019

Structural Graph Representations based on Multiscale Local Network Topologies.

Felix Borutta, Julian Busch, Evgeniy Faerman, Adina Klink, Matthias Schubert

Proceedings of the 2019 IEEE/WIC/ACM International Conference on Web Intelligence, 2019

2018

Semi-Supervised Learning on Graphs Based on Local Label Distributions.

Evgheniy Faerman, Felix Borutta, Julian Busch, Matthias Schubert

CoRR, 2018