Johannes F. Lutzeyer

According to our database, Johannes F. Lutzeyer authored at least 15 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Hyper-Heuristics Can Profit From Global Variation Operators.

Benjamin Doerr, Johannes F. Lutzeyer

CoRR, 2024

Understanding Virtual Nodes: Oversmoothing, Oversquashing, and Node Heterogeneity.

Joshua Southern, Francesco Di Giovanni, Michael M. Bronstein, Johannes F. Lutzeyer

CoRR, 2024

Graph Neural Machine: A New Model for Learning with Tabular Data.

Giannis Nikolentzos, Siyun Wang, Johannes F. Lutzeyer, Michalis Vazirgiannis

CoRR, 2024

Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks.

Yassine Abbahaddou, Sofiane Ennadir, Johannes F. Lutzeyer, Michalis Vazirgiannis, Henrik Boström

Proceedings of the Twelfth International Conference on Learning Representations, 2024

A Simple and Yet Fairly Effective Defense for Graph Neural Networks.

Sofiane Ennadir, Yassine Abbahaddou, Johannes F. Lutzeyer, Michalis Vazirgiannis, Henrik Boström

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Path Neural Networks: Expressive and Accurate Graph Neural Networks.

Gaspard Michel, Giannis Nikolentzos, Johannes F. Lutzeyer, Michalis Vazirgiannis

Proceedings of the International Conference on Machine Learning, 2023

How the Move Acceptance Hyper-Heuristic Copes With Local Optima: Drastic Differences Between Jumps and Cliffs.

Benjamin Doerr, Arthur Dremaux, Johannes F. Lutzeyer, Aurélien Stumpf

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Graph Ordering Attention Networks.

Michail Chatzianastasis, Johannes F. Lutzeyer, George Dasoulas, Michalis Vazirgiannis

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Modularity-aware graph autoencoders for joint community detection and link prediction.

Guillaume Salha-Galvan, Johannes F. Lutzeyer, George Dasoulas, Romain Hennequin, Michalis Vazirgiannis

Neural Networks, 2022

New Frontiers in Graph Autoencoders: Joint Community Detection and Link Prediction.

Guillaume Salha-Galvan, Johannes F. Lutzeyer, George Dasoulas, Romain Hennequin, Michalis Vazirgiannis

CoRR, 2022

Improving Graph Neural Networks at Scale: Combining Approximate PageRank and CoreRank.

Ariel R. Ramos Vela, Johannes F. Lutzeyer, Anastasios Giovanidis, Michalis Vazirgiannis

CoRR, 2022

Sparsifying the Update Step in Graph Neural Networks.

Johannes F. Lutzeyer, Changmin Wu, Michalis Vazirgiannis

Proceedings of the Topological, 2022

Node Feature Kernels Increase Graph Convolutional Network Robustness.

Mohamed El Amine Seddik, Changmin Wu, Johannes F. Lutzeyer, Michalis Vazirgiannis

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Learning Parametrised Graph Shift Operators.

George Dasoulas, Johannes F. Lutzeyer, Michalis Vazirgiannis

Proceedings of the 9th International Conference on Learning Representations, 2021

2019

Comparing Spectra of Graph Shift Operator Matrices.

Johannes F. Lutzeyer, Andrew T. Walden

Proceedings of the Complex Networks and Their Applications VIII, 2019