Attila Lischka

According to our database, Attila Lischka authored at least 8 papers between 2024 and 2026.

Collaborative distances:

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

2026

GREAT-EER: Graph Edge Attention Network for Emergency Evacuation Responses.

Attila Lischka, Balázs Kulcsár

CoRR, February, 2026

Learning to Dial-a-Ride: A Deep Graph Reinforcement Learning Approach to the Electric Dial-a-Ride Problem.

Sten Elling Tingstad Jacobsen, Attila Lischka, Balázs Kulcsár, Anders Lindman

CoRR, January, 2026

2025

Towards Reproducibility in Predictive Process Mining: SPICE - A Deep Learning Library.

Oliver Stritzel, Nick Hühnerbein, Simon Rauch, Itzel Zarate, Lukas Fleischmann, Moike Buck, Attila Lischka, Christian M. M. Frey

CoRR, December, 2025

Learning for routing: A guided review of recent developments and future directions.

Fangting Zhou, Attila Lischka, Balázs Kulcsár, Jiaming Wu, Morteza Haghir Chehreghani, Gilbert Laporte

CoRR, July, 2025

Learning to Solve Multi-Objective Routing Problems on Multigraphs.

Filip Rydin, Attila Lischka, Jiaming Wu, Morteza Haghir Chehreghani, Balázs Kulcsár

CoRR, June, 2025

Directly Follows Graphs Go Predictive Process Monitoring With Graph Neural Networks.

Attila Lischka, Simon Rauch, Oliver Stritzel

CoRR, March, 2025

2024

A GREAT Architecture for Edge-Based Graph Problems Like TSP.

Attila Lischka, Jiaming Wu, Morteza Haghir Chehreghani, Balázs Kulcsár

CoRR, 2024

Less Is More - On the Importance of Sparsification for Transformers and Graph Neural Networks for TSP.

Attila Lischka, Jiaming Wu, Rafael Basso, Morteza Haghir Chehreghani, Balázs Kulcsár

CoRR, 2024