Dr.
Lukas Faber

Publications

GraphChef: Decision-Tree Recipes to Explain Graph Neural Networks
Peter Müller, Lukas Faber, Karolis Martinkus and Roger Wattenhofer.
12th International Conference on Learning Representations (ICLR), Vienna, Austria, May 2024.
BibTeX
GwAC: GNNs with Asynchronous Communication
Lukas Faber and Roger Wattenhofer.
2nd Learning on Graphs Conference (LoG), Virtual, November 2023.
BibTeX
GraphChef: Learning the Recipe of Your Dataset
Peter Müller, Lukas Faber, Karolis Martinkus and Roger Wattenhofer.
Workshop on Interpretable ML in Healthcare at International Conference on Machine Learning, Honolulu, Hawaii, July 2023.
BibTeX
Neural Status Registers
Lukas Faber and Roger Wattenhofer.
International Conference on Machine Learning (ICML), Honolulu, Hawaii, July 2023.
BibTeX
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks (Spotlight)
Pál András Papp, Karolis Martinkus, Lukas Faber and Roger Wattenhofer.
35th Conference on Neural Information Processing Systems (NeurIPS), Virtual, December 2021.
BibTeX
When Comparing to Ground Truth is Wrong: On Evaluating GNN Explanation Methods
Lukas Faber, Amin K. Moghaddam and Roger Wattenhofer.
27th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Virtual, August 2021.
External BibTeX
Towards Robust Graph Contrastive Learning
Nikola Jovanovic, Zhao Meng, Lukas Faber and Roger Wattenhofer.
Workshop on Self-Supervised Learning for the Web (SSL@WWW 2021), Online, April 2021.
BibTeX
Learning Lower Bounds for Graph Exploration With Reinforcement Learning
Jorel Elmiger, Lukas Faber, Pankaj Khanchandani, Oliver Richter and Roger Wattenhofer.
Learning meets Combinatorial Algorithms Workshop @ NeurIPS 2020, online, December 2020.
BibTeX
Medley2K: A Dataset of Medley Transitions
Lukas Faber, Sandro Luck, Damian Pascual, Andreas Roth, Gino Brunner and Roger Wattenhofer.
13th International Workshop on Machine Learning and Music (MML at ECML-PKDD), Ghent, Belgium, September 2020.
BibTeX
Contrastive GNN Explanation
Lukas Faber, Amin K. Moghaddam and Roger Wattenhofer.
Graph Representation Learning and Beyond Workshop (GRL+ at ICML), July 2020.
BibTeX
Personalized Knowledge Graph Summarization: From the Cloud to Your Pocket
Tara Safavi, Caleb Belth, Lukas Faber, Davide Mottin, Emmanuel Müller and Danai Koutra.
International Conference on Data Mining (ICDM), Beijing, China, November 2019.
BibTeX
A Tissue-aware Gene Selection Approach for Analyzing Multi-tissue Gene Expression Data
Cindy Perscheid, Lukas Faber, Milena Kraus, Paul Arndt, Michael Janke, Sebastian Rehfeldt, Antje Schubotz, Tamara Slosarek and Matthias Uflacker.
International Conference on Bioinformatics and Biomedicine (BIBM), Madrid, Spain, December 2018.
BibTeX
Low Redundancy Estimation of Correlation Matrices for Time Series using Triangular Bounds
Erik Scharwächter, Fabian Geier, Lukas Faber and Emmanuel Müller.
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Melbourne, Australia, May 2018.
BibTeX
Serving Live Multimedia for the Linked Open Data Cloud
Sebastian Serth, Stephan Haarmann and Lukas Faber.
Jahrestagung der Gesellschaft für Informatik, Chemnitz, Germany, September 2017.
BibTeX

Theses & Labs

	Title	Type	Contact/Supervisor	Assigned	Student(s)
Past Theses & Labs
	Developing Interpretable Graph Neural Networks for High Dimensional Feature Spaces	B	Karolis Martinkus, Lukas Faber	HS 22
	Distributed Asynchronous Policy (DAP) with RL [confidential]	M	Karolis Martinkus, Lukas Faber	HS 21
	Interpretable Graph Neural Network [confidential]	M	Karolis Martinkus, Lukas Faber	HS 21
	Enhancing Graph Neural Networks with Boosting	B	Lukas Faber, Karolis Martinkus	FS 21
	Towards Robust Graph Contrastive Learning [confidential]	S	Lukas Faber, Zhao Meng	HS 20
	Development of a Decentralised Communication Framework for an Online Tichu Game	S	Lukas Faber, Oliver Richter	HS 20
	Explaining and Visualizing Graph Neural Networks [confidential]	M	Lukas Faber	HS 20
	Graph Neural Networks in Finance	S	Lukas Faber, Béni Egressy	HS 20
	Multiagent Reinforcement Learning in Financial Networks	S	Lukas Faber, Pál András Papp	HS 20
	Attribution Methods for Understanding and Visualizing Graph Neural Networks [confidential]	S	Lukas Faber	FS 20
	Reinforcement Learning in Graph Theory [confidential]	B	Pankaj Khanchandani, Lukas Faber	FS 20
	Tichu Bot	S	Lukas Faber, Zeta Avarikioti	FS 20
	Understanding and Visualizing Graph Neural Networks	S	Lukas Faber	FS 20
	Music Medley Generation [confidential]	G	Damian Pascual, Lukas Faber	HS 19	,

Dr. Lukas Faber

Publications

Theses & Labs

Past Theses & Labs

Dr.
Lukas Faber