WBCsvm: Weighted Bayesian Classification based on Support Vector Machines. - Thomas Gärtner 001; Peter A. Flach (ICML, 2001)

Multi-Instance Kernels. - Thomas Gärtner 001; Peter A. Flach; Adam Kowalczyk; Alexander J. Smola (ICML, 2002)

Kernels for Structured Data. - Thomas Gärtner 001; John W. Lloyd; Peter A. Flach (ILP, 2002)

On Graph Kernels: Hardness Results and Efficient Alternatives. - Thomas Gärtner 001; Peter A. Flach; Stefan Wrobel (COLT, 2003)

A survey of kernels for structured data. - Thomas Gärtner 001 (SIGKDD Explor., 2003)

Fisher Kernels for Logical Sequences. - Kristian Kersting; Thomas Gärtner 001 (ECML, 2004)

Cyclic pattern kernels for predictive graph mining. - Tamás Horváth 001; Thomas Gärtner 001; Stefan Wrobel (KDD, 2004)

Kernels and Distances for Structured Data. - Thomas Gärtner 001; John W. Lloyd; Peter A. Flach (Mach. Learn., 2004)

Kernels for structured data. - Thomas Gärtner 001 (2005)

Kernels for Predictive Graph Mining. - Stefan Wrobel; Thomas Gärtner 001; Tamás Horváth 001 (GfKl, 2005)

Kernfunktionen für Strukturierte Daten. - Thomas Gärtner 001 (Ausgezeichnete Informatikdissertationen, 2005)

Large-Scale Multiclass Transduction. - Thomas Gärtner 001; Quoc V. Le; Simon Burton 003; Alexander J. Smola; S. V. N. Vishwanathan (NIPS, 2005)

Transductive Gaussian Process Regression with Automatic Model Selection. - Quoc V. Le; Alexander J. Smola; Thomas Gärtner 001; Yasemin Altun (ECML, 2006)

Efficient co-regularised least squares regression. - Ulf Brefeld; Thomas Gärtner 001; Tobias Scheffer; Stefan Wrobel (ICML, 2006)

Simpler knowledge-based support vector machines. - Quoc V. Le; Alexander J. Smola; Thomas Gärtner 001 (ICML, 2006)

Graph kernels and Gaussian processes for relational reinforcement learning. - Kurt Driessens; Jan Ramon; Thomas Gärtner 001 (Mach. Learn., 2006)

The Cost of Learning Directed Cuts. - Thomas Gärtner 001; Gemma C. Garriga (ECML, 2007)

Efficient Kernel Methods for Graphs. - Thomas Gärtner 001 (MLG, 2007)

Semidefinite Ranking on Graphs. - Shankar Vembu; Thomas Gärtner 001; Stefan Wrobel (MLG, 2007)

Regularization path for Ranking SVM. - Karina Zapien Arreola; Thomas Gärtner 001; Gilles Gasso; Stéphane Canu (ESANN, 2008)

Towards Engaging Games. - Olana Missura; Kristian Kersting; Thomas Gärtner 001 (LWA, 2008)

Support-Vector-Machine-Based Ranking Significantly Improves the Effectiveness of Similarity Searching Using 2D Fingerprints and Multiple Reference Compounds. - Hanna Geppert; Tamás Horváth 001; Thomas Gärtner 001; Stefan Wrobel; Jürgen Bajorath (J. Chem. Inf. Model., 2008)

Kernels for Structured Data - Thomas Gärtner 001 (WorldScientific, 2008)

On the Complexity of Constraint-Based Theory Extraction. - Mario Boley; Thomas Gärtner 001 (Discovery Science, 2009)

Context-Based Clustering of Image Search Results. - Hongqi Wang; Olana Missura; Thomas Gärtner 001; Stefan Wrobel (KI, 2009)

Player Modeling for Intelligent Difficulty Adjustment. - Olana Missura; Thomas Gärtner 001 (LWA, 2009)

Classification on Graphs for Dynamic Difficulty Adjustment: More Questions Than Answers. - Olana Missura; Thomas Gärtner 001 (MLG/SRL@ILP, 2009)

MAP Structured Prediction by Sampling. - Shankar Vembu; Thomas Gärtner 001; Mario Boley (MLG/SRL@ILP, 2009)

Probabilistic Structured Predictors. - Shankar Vembu; Thomas Gärtner 001; Mario Boley (UAI, 2009)

Ligand Prediction from Protein Sequence and Small Molecule Information Using Support Vector Machines and Fingerprint Descriptors. - Hanna Geppert; Jens Humrich; Dagmar Stumpfe; Thomas Gärtner 001; Jürgen Bajorath (J. Chem. Inf. Model., 2009)

Guest editors' introduction: special issue on mining and learning with graphs. - Thomas Gärtner 001; Gemma C. Garriga (Mach. Learn., 2009)

On structured output training: hard cases and an efficient alternative. - Thomas Gärtner 001; Shankar Vembu (Mach. Learn., 2009)

Label Ranking Algorithms: A Survey. - Shankar Vembu; Thomas Gärtner 001 (Preference Learning, 2010)

On-Line Handwriting Recognition with Parallelized Machine Learning Algorithms. - Sebastian Bothe; Thomas Gärtner 001; Stefan Wrobel (KI, 2010)

Counting-based Output Prediction for Orphan Screening. - Katrin Ullrich; Christoph Stahr; Thomas Gärtner 001 (LWA, 2010)

Formal Concept Sampling for Counting and Threshold-Free Local Pattern Mining. - Mario Boley; Thomas Gärtner 001; Henrik Grosskreutz (SDM, 2010)

Graph Kernels. - Thomas Gärtner 001; Tamás Horváth 001; Stefan Wrobel (Encyclopedia of Machine Learning, 2010)

A Fixed Parameter Tractable Integer Program for Finding the Maximum Order Preserving Submatrix. - Jens Humrich; Thomas Gärtner 001; Gemma C. Garriga (ICDM, 2011)

Direct local pattern sampling by efficient two-step random procedures. - Mario Boley; Claudio Lucchese; Daniel Paurat; Thomas Gärtner 001 (KDD, 2011)

Direct Pattern Sampling with Respect to Pattern Frequency. - Mario Boley; Claudio Lucchese; Daniel Paurat; Thomas Gärtner 001 (LWA, 2011)

Predicting Dynamic Difficulty. - Olana Missura; Thomas Gärtner 001 (NIPS, 2011)

Dynamic difficulty for checkers and Chinese chess. - Laurentiu Ilici; Jiaojian Wang; Olana Missura; Thomas Gärtner 001 (CIG, 2012)

Linear space direct pattern sampling using coupling from the past. - Mario Boley; Sandy Moens; Thomas Gärtner 001 (KDD, 2012)

Beating Human Analysts in Nowcasting Corporate Earnings by Using Publicly Available Stock Price and Correlation Features. - Michael Kamp; Mario Boley; Thomas Gärtner 001 (ICDM Workshops, 2013)

InVis: A Tool for Interactive Visual Data Analysis. - Daniel Paurat; Thomas Gärtner 001 (ECML/PKDD (3), 2013)

Predicting unexpected influxes of players in EVE online. - Roman Garnett; Thomas Gärtner 001; Timothy Ellersiek; Eyjolfur Gudmondsson; Petur Oskarsson (CIG, 2014)

Interactive Knowledge-Based Kernel PCA. - Dino Oglic; Daniel Paurat; Thomas Gärtner 001 (ECML/PKDD (2), 2014)

Introducing the 'active search' method for iterative virtual screening. - Roman Garnett; Thomas Gärtner 001; Martin Vogt 001; Jürgen Bajorath (J. Comput. Aided Mol. Des., 2015)

Ligand-Based Virtual Screening with Co-regularised Support Vector Regression. - Katrin Ullrich; Michael Kamp; Thomas Gärtner 001; Martin Vogt 001; Stefan Wrobel (ICDM Workshops, 2016)

Greedy Feature Construction. - Dino Oglic; Thomas Gärtner 001 (NIPS, 2016)

Guest editors' introduction to the EcmlPkdd 2016 journal track special issue of Machine Learning. - Thomas Gärtner 001; Mirco Nanni; Andrea Passerini; Céline Robardet (Mach. Learn., 2016)

Active Search in Intensionally Specified Structured Spaces. - Dino Oglic; Roman Garnett; Thomas Gärtner 001 (AAAI, 2017)

Nyström Method with Kernel K-means++ Samples as Landmarks. - Dino Oglic; Thomas Gärtner 001 (ICML, 2017)

Effective Parallelisation for Machine Learning. - Michael Kamp; Mario Boley; Olana Missura; Thomas Gärtner 001 (NIPS, 2017)

Co-Regularised Support Vector Regression. - Katrin Ullrich; Michael Kamp; Thomas Gärtner 001; Martin Vogt 001; Stefan Wrobel (ECML/PKDD (2), 2017)

Graph Kernels. - Thomas Gärtner 001; Tamás Horváth 001; Stefan Wrobel (Encyclopedia of Machine Learning and Data Mining, 2017)

Learning in Reproducing Kernel Krein Spaces. - Dino Oglic; Thomas Gärtner 001 (ICML, 2018)

Large Scale Learning with Kreĭn Kernels. - Dino Oglic; Thomas Gärtner 001 (CoRR, 2018)

Corresponding Projections for Orphan Screening. - Sven Giesselbach; Katrin Ullrich; Michael Kamp; Daniel Paurat; Thomas Gärtner 001 (CoRR, 2018)

Scalable Learning in Reproducing Kernel Krein Spaces. - Dino Oglic; Thomas Gärtner 001 (ICML, 2019)

Interactive Machine Learning with Structured Data. - Thomas Gärtner 001 (LWDA, 2020)

Active Learning of Convex Halfspaces on Graphs. - Maximilian Thiessen; Thomas Gärtner 001 (NeurIPS, 2021)

Online Learning of Convex Sets on Graphs. - Maximilian Thiessen; Thomas Gärtner 001 (ECML/PKDD (4), 2022)

Kernel Methods for Predicting Yields of Chemical Reactions. - Alexe L. Haywood; Joseph Redshaw; Magnus W. D. Hanson-Heine; Adam Taylor; Alex Brown; Andrew M. Mason; Thomas Gärtner 001; Jonathan D. Hirst (J. Chem. Inf. Model., 2022)

Expectation-Complete Graph Representations with Homomorphisms. - Pascal Welke; Maximilian Thiessen; Fabian Jogl; Thomas Gärtner 001 (ICML, 2023)

Expressivity-Preserving GNN Simulation. - Fabian Jogl; Maximilian Thiessen; Thomas Gärtner 001 (NeurIPS, 2023)

Improving Expert Specialization in Mixture of Experts. - Yamuna Krishnamurthy; Chris Watkins; Thomas Gärtner 001 (CoRR, 2023)

The Expressive Power of Path-Based Graph Neural Networks. - Caterina Graziani; Tamara Drucks; Fabian Jogl; Monica Bianchini; Franco Scarselli; Thomas Gärtner 001 (ICML, 2024)

Logical Distillation of Graph Neural Networks. - Alexander Pluska; Pascal Welke; Thomas Gärtner 001; Sagar Malhotra (KR, 2024)

Scalable Interactive Data Visualization. - Florian Chen; Thomas Gärtner 001 (ECML/PKDD (8), 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 001; Haggai Maron (CoRR, 2024)

Reaction rebalancing: a novel approach to curating reaction databases. - Tieu-Long Phan; Klaus Weinbauer; Thomas Gärtner 001; Daniel Merkle; Jakob L. Andersen; Rolf Fagerberg; Peter F. Stadler (J. Cheminformatics, 2024)

Maximally Expressive GNNs for Outerplanar Graphs. - Franka Bause; Fabian Jogl; Patrick Indri; Tamara Drucks; David Penz; Nils Morten Kriege; Thomas Gärtner 001; Pascal Welke; Maximilian Thiessen (Trans. Mach. Learn. Res., 2025)

On Finding All Connected Maximum-Sized Common Subgraphs in Multiple Labeled Graphs. - Johannes B. S. Petersen; Akbar Davoodi; Thomas Gärtner 001; Marc Hellmuth; Daniel Merkle (CoRR, 2025)

WILTing Trees: Interpreting the Distance Between MPNN Embeddings. - Masahiro Negishi; Thomas Gärtner 001; Pascal Welke (CoRR, 2025)