Gärtner, Thomas

45 publications

TMLR 2025 Maximally Expressive GNNs for Outerplanar Graphs Franka Bause, Fabian Jogl, Patrick Indri, Tamara Drucks, David Penz, Nils Morten Kriege, Thomas Gärtner, Pascal Welke, Maximilian Thiessen

TMLR 2025 On the Challenges and Opportunities in Generative AI Laura Manduchi, Clara Meister, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin

ICML 2025 Probably Approximately Global Robustness Certification Peter Blohm, Patrick Indri, Thomas Gärtner, Sagar Malhotra

ICML 2025 WILTing Trees: Interpreting the Distance Between MPNN Embeddings Masahiro Negishi, Thomas Gärtner, Pascal Welke

ICMLW 2024 Distillation Based Robustness Verification with PAC Guarantees Patrick Indri, Peter Blohm, Anagha Athavale, Ezio Bartocci, Georg Weissenbacher, Matteo Maffei, Dejan Nickovic, Thomas Gärtner, Sagar Malhotra

NeurIPSW 2024 Is Expressivity Essential for the Predictive Performance of Graph Neural Networks? Fabian Jogl, Pascal Welke, Thomas Gärtner

ICMLW 2024 Logical Distillation of Graph Neural Networks Alexander Pluska, Pascal Welke, Thomas Gärtner, Sagar Malhotra

ECML-PKDD 2024 Scalable Interactive Data Visualization Florian Chen, Thomas Gärtner

ICML 2024 The Expressive Power of Path-Based Graph Neural Networks Caterina Graziani, Tamara Drucks, Fabian Jogl, Monica Bianchini, Franco Scarselli, Thomas Gärtner

NeurIPSW 2024 Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs Fabrizio Frasca, Fabian Jogl, Moshe Eliasof, Matan Ostrovsky, Carola-Bibiane Schönlieb, Thomas Gärtner, Haggai Maron

ICLRW 2023 Can Stochastic Weight Averaging Improve Generalization in Private Learning? Patrick Indri, Tamara Drucks, Thomas Gärtner

ICML 2023 Expectation-Complete Graph Representations with Homomorphisms Pascal Welke, Maximilian Thiessen, Fabian Jogl, Thomas Gärtner

NeurIPS 2023 Expressivity-Preserving GNN Simulation Fabian Jogl, Maximilian Thiessen, Thomas Gärtner

NeurIPSW 2023 Maximally Expressive GNNs for Outerplanar Graphs Franka Bause, Fabian Jogl, Patrick Indri, Tamara Drucks, David Penz, Nils Kriege, Thomas Gärtner, Pascal Welke, Maximilian Thiessen

NeurIPSW 2023 No PAIN No Gain: More Expressive GNNs with Paths Caterina Graziani, Tamara Drucks, Monica Bianchini, Franco Scarselli, Thomas Gärtner

NeurIPSW 2022 Expectation Complete Graph Representations Using Graph Homomorphisms Maximilian Thiessen, Pascal Welke, Thomas Gärtner

ECML-PKDD 2022 Online Learning of Convex Sets on Graphs Maximilian Thiessen, Thomas Gärtner

ICLRW 2022 Reducing Learning on Cell Complexes to Graphs Fabian Jogl, Maximilian Thiessen, Thomas Gärtner

NeurIPSW 2021 Controllable Network Data Balancing with GANs Fares Meghdouri, Thomas Schmied, Thomas Gärtner, Tanja Zseby

ICML 2019 Scalable Learning in Reproducing Kernel Krein Spaces Dino Oglic, Thomas Gärtner

ECML-PKDD 2018 Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings, Part I Michele Berlingerio, Francesco Bonchi, Thomas Gärtner, Neil Hurley, Georgiana Ifrim

ECML-PKDD 2018 Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings, Part II Michele Berlingerio, Francesco Bonchi, Thomas Gärtner, Neil Hurley, Georgiana Ifrim

AAAI 2017 Active Search in Intensionally Specified Structured Spaces Dino Oglic, Roman Garnett, Thomas Gärtner

ECML-PKDD 2017 Co-Regularised Support Vector Regression Katrin Ullrich, Michael Kamp, Thomas Gärtner, Martin Vogt, Stefan Wrobel

NeurIPS 2017 Effective Parallelisation for Machine Learning Michael Kamp, Mario Boley, Olana Missura, Thomas Gärtner

ICML 2017 Nyström Method with Kernel K-Means++ Samples as Landmarks Dino Oglic, Thomas Gärtner

NeurIPS 2016 Greedy Feature Construction Dino Oglic, Thomas Gärtner

MLJ 2016 Guest Editors' Introduction to the EcmlPkdd 2016 Journal Track Special Issue of Machine Learning Thomas Gärtner, Mirco Nanni, Andrea Passerini, Céline Robardet

ECML-PKDD 2014 Interactive Knowledge-Based Kernel PCA Dino Oglic, Daniel Paurat, Thomas Gärtner

ECML-PKDD 2013 InVis: A Tool for Interactive Visual Data Analysis Daniel Paurat, Thomas Gärtner

NeurIPS 2011 Predicting Dynamic Difficulty Olana Missura, Thomas Gärtner

MLJ 2009 Guest Editors' Introduction: Special Issue on Mining and Learning with Graphs Thomas Gärtner, Gemma C. Garriga

ECML-PKDD 2009 On Structured Output Training: Hard Cases and an Efficient Alternative Thomas Gärtner, Shankar Vembu

MLJ 2009 On Structured Output Training: Hard Cases and an Efficient Alternative Thomas Gärtner, Shankar Vembu

UAI 2009 Probabilistic Structured Predictors Shankar Vembu, Thomas Gärtner, Mario Boley

ICML 2006 Efficient Co-Regularised Least Squares Regression Ulf Brefeld, Thomas Gärtner, Tobias Scheffer, Stefan Wrobel

MLJ 2006 Graph Kernels and Gaussian Processes for Relational Reinforcement Learning Kurt Driessens, Jan Ramon, Thomas Gärtner

ICML 2006 Simpler Knowledge-Based Support Vector Machines Quoc V. Le, Alexander J. Smola, Thomas Gärtner

ECML-PKDD 2006 Transductive Gaussian Process Regression with Automatic Model Selection Quoc V. Le, Alexander J. Smola, Thomas Gärtner, Yasemin Altun

NeurIPS 2005 Large-Scale Multiclass Transduction Thomas Gärtner, Quoc V. Le, Simon Burton, Alex J. Smola, Vishy Vishwanathan

ECML-PKDD 2004 Fisher Kernels for Logical Sequences Kristian Kersting, Thomas Gärtner

MLJ 2004 Kernels and Distances for Structured Data Thomas Gärtner, John W. Lloyd, Peter A. Flach

COLT 2003 On Graph Kernels: Hardness Results and Efficient Alternatives Thomas Gärtner, Peter A. Flach, Stefan Wrobel

ICML 2002 Multi-Instance Kernels Thomas Gärtner, Peter A. Flach, Adam Kowalczyk, Alexander J. Smola

ICML 2001 WBCsvm: Weighted Bayesian Classification Based on Support Vector Machines Thomas Gärtner, Peter A. Flach