| 2026 | AAAI | The Tatort Test of Intelligence: Towards Narrative Comprehension as a Benchmark for AI. | Stefan Kramer, Lennart Baur, Lars Reinhardt |
| 2025 | DIS | Prompting Neural-Guided Equation Discovery Based on Residuals. | Jannis Brugger, Viktor Pfanschilling, David Richter, Mira Mezini, Stefan Kramer |
| 2025 | DIS | Exploring the Design Space of Fair Tree Learning Algorithms. | Kiara Stempel, Mattia Cerrato, Stefan Kramer |
| 2025 | ICCS | cuTeBool: Fast and Scalable Boolean Matrix Factorization on GPUs Using Tensor Cores. | Andrea Beyer, Valentin Henkys, Robin Kobus, Stefan Kramer, Bertil Schmidt |
| 2025 | IDA | Integrating Inverse and Forward Modeling for Sparse Temporal Data from Sensor Networks. | Julian Vexler, Bjrn Vieten, Martin Nelke, Stefan Kramer |
| 2024 | AAAI | Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations. | Cedric Derstroff, Mattia Cerrato, Jannis Brugger, Jan Peters, Stefan Kramer |
| 2024 | BMVC | Patchhealer: Counterfactual Image Segment Transplants with chest X-ray domain check. | Hakan Lane, Michal Valko, Veda Sahaja Bandi, Nandini Lokesh Reddy, Stefan Kramer |
| 2024 | BMVC | CardioCNN: Gamification of counterfactual image transplants. | Hakan Lane, Michal Valko, Stefan Kramer |
| 2024 | DIS | Residuals for Equation Discovery. | Jannis Brugger, Viktor Pfanschilling, Mira Mezini, Stefan Kramer |
| 2024 | DIS | Science-Gym: A Simple Testbed for AI-Driven Scientific Discovery. | Mattia Cerrato, Nicholas Schmitt, Lennart Baur, Edward Finkelstein, Selina Jukic, Lars Mnzel, Felix Peter Paul, Pascal Pfannes, Benedikt Rohr, Julius Schellenberg, Philipp Wolf, Stefan Kramer |
| 2024 | DIS | Soft Hoeffding Tree: A Transparent and Differentiable Model on Data Streams. | Kirsten Kbschall, Lisa Hartung, Stefan Kramer |
| 2024 | DIS | FairTrader: A Method to Smoothly Control the Performance-Fairness Trade-Off. | Kiara Stempel, Stefan Kramer |
| 2024 | FAW | Active Learning Supported Iterative Combinatorial Auctions. | Benjamin Estermann, Stefan Kramer, Roger Wattenhofer, Kanye Ye Wang |
| 2023 | AAAI | Invariant Representations with Stochastically Quantized Neural Networks. | Mattia Cerrato, Marius Kppel, Roberto Esposito, Stefan Kramer |
| 2023 | DIS | Privacy-Preserving Learning of Random Forests Without Revealing the Trees. | Lukas-Malte Bammert, Stefan Kramer, Mattia Cerrato, Ernst Althaus |
| 2023 | ECAI | Classifying Aircraft Categories from Magnetometry Data Using a Hypotheses-Based Multi-Task Framework. | Julian Vexler, Stefan Kramer |
| 2023 | FUSION | Identifying Aircraft Motions and Patterns from Magnetometry Data Using a Knowledge-Based Multi-Fusion Approach. | Julian Vexler, Stefan Kramer |
| 2021 | ENASE | Myths and Misconceptions about Machine Learning and How They Are Related to Software Engineering. | Stefan Kramer |
| 2020 | DSAA | Fair pairwise learning to rank. | Mattia Cerrato, Marius Kppel, Alexander Segner, Roberto Esposito, Stefan Kramer |
| 2020 | IJCAI | A Brief History of Learning Symbolic Higher-Level Representations from Data (And a Curious Look Forward). | Stefan Kramer |
| 2020 | PSB | Towards Identifying Drug Side Effects from Social Media Using Active Learning andCrowd Sourcing. | Sophie Burkhardt, Julia Siekiera, Josua Glodde, Miguel A. Andrade-Navarro, Stefan Kramer |
| 2019 | CEC | Exploring Multi-Objective Optimization for Multi-Label Classifier Ensembles. | Sriparna Saha, Debanjan Sarkar, Stefan Kramer |
| 2019 | DIS | Integrating LSTMs with Online Density Estimation for the Probabilistic Forecast of Energy Consumption. | Julian Vexler, Stefan Kramer |
| 2018 | DASFAA | Graph Clustering with Local Density-Cut. | Junming Shao, Qinli Yang, Zhong Zhang, Jinhu Liu, Stefan Kramer |
| 2018 | DSAA | Towards Bankruptcy Prediction: Deep Sentiment Mining to Detect Financial Distress from Business Management Reports. | Zahra Ahmadi, Peter Martens, Christopher Koch, Thomas Gottron, Stefan Kramer |
| 2018 | DSAA | Forest of Normalized Trees: Fast and Accurate Density Estimation of Streaming Data. | Patrick Rehn, Zahra Ahmadi, Stefan Kramer |
| 2018 | ICPADS | cuBool: Bit-Parallel Boolean Matrix Factorization on CUDA-Enabled Accelerators. | Robin Kobus, Adrian Lamoth, Andr Mller, Christian Hundt, Stefan Kramer, Bertil Schmidt |
| 2018 | SPLC | An inductive learning perspective on automated generation of feature models from given product specifications. | Hermann Kaindl, Stefan Kramer, Ralph Hoch |
| 2017 | AIME | Convolutional Neural Networks for the Identification of Regions of Interest in PET Scans: A Study of Representation Learning for Diagnosing Alzheimer's Disease. | Andreas Karwath, Markus Hubrich, Stefan Kramer |
| 2017 | DIS | An In-Depth Experimental Comparison of RNTNs and CNNs for Sentence Modeling. | Zahra Ahmadi, Marcin Skowron, Aleksandrs Stier, Stefan Kramer |
| 2016 | PAKDD | A Nonlinear Label Compression and Transformation Method for Multi-label Classification Using Autoencoders. | Jrg Wicker, Andrey Tyukin, Stefan Kramer |
| 2016 | SAC | Trading off accuracy for efficiency by randomized greedy warping. | Atif Raza, Jrg Wicker, Stefan Kramer |
| 2015 | DSAA | Modeling recurrent distributions in streams using possible worlds. | Michael Geilke, Andreas Karwath, Stefan Kramer |
| 2015 | KDD | Cinema Data Mining: The Smell of Fear. | Jrg Wicker, Nicolas Krauter, Bettina Derstorff, Christof Stnner, Efstratios Bourtsoukidis, Thomas Klpfel, Jonathan Williams, Stefan Kramer |
| 2015 | SAC | On the spectrum between binary relevance and classifier chains in multi-label classification. | Sophie Burkhardt, Stefan Kramer |
| 2015 | SAC | Alternating model trees. | Eibe Frank, Michael Mayo, Stefan Kramer |
| 2014 | DSAA | A probabilistic condensed representation of data for stream mining. | Michael Geilke, Andreas Karwath, Stefan Kramer |
| 2014 | ECAI | Constrained Latent Dirichlet Allocation for Subgroup Discovery with Topic Rules. | Rui Li, Zahra Ahmadi, Stefan Kramer |
| 2014 | KDD | Prototype-based learning on concept-drifting data streams. | Junming Shao, Zahra Ahmadi, Stefan Kramer |
| 2014 | SAC | Structural clustering of millions of molecular graphs. | Madeleine Seeland, Andreas Karwath, Stefan Kramer |
| 2014 | SAC | Extracting information from support vector machines for pattern-based classification. | Madeleine Seeland, Andreas Maunz, Andreas Karwath, Stefan Kramer |
| 2013 | ICDM | Online Estimation of Discrete Densities. | Michael Geilke, Eibe Frank, Andreas Karwath, Stefan Kramer |
| 2013 | SAC | Incremental linear model trees on massive datasets: keep it simple, keep it fast. | Andreas Hapfelmeier, Jana Schmidt, Stefan Kramer |
| 2013 | SAC | Model selection based product kernel learning for regression on graphs. | Madeleine Seeland, Stefan Kramer, Bernhard Pfahringer |
| 2012 | DIS | Efficient Redundancy Reduced Subgroup Discovery via Quadratic Programming. | Rui Li, Stefan Kramer |
| 2012 | ICDM | Online Induction of Probabilistic Real Time Automata. | Jana Schmidt, Stefan Kramer |
| 2012 | KDD | A structural cluster kernel for learning on graphs. | Madeleine Seeland, Andreas Karwath, Stefan Kramer |
| 2012 | SAC | Maximum Common Subgraph based locally weighted regression. | Madeleine Seeland, Fabian Buchwald, Stefan Kramer, Bernhard Pfahringer |
| 2012 | SAC | Multi-label classification using boolean matrix decomposition. | Jrg Wicker, Bernhard Pfahringer, Stefan Kramer |
| 2012 | SDM | Scalable Induction of Probabilistic Real-Time Automata Using Maximum Frequent Pattern Based Clustering. | Jana Schmidt, Sonja Ansorge, Stefan Kramer |
| 2011 | AIME | A Case Study of Stacked Multi-view Learning in Dementia Research. | Rui Li, Andreas Hapfelmeier, Jana Schmidt, Robert Perneczky, Alexander Drzezga, Alexander Kurz, Stefan Kramer |
| 2011 | DIS | The Augmented Itemset Tree: A Data Structure for Online Maximum Frequent Pattern Mining. | Jana Schmidt, Stefan Kramer |
| 2011 | ICDM | Clustering with Attribute-Level Constraints. | Jana Schmidt, Elisabeth Maria Brndle, Stefan Kramer |
| 2010 | AAAI | Fast Conditional Density Estimation for Quantitative Structure-Activity Relationships. | Fabian Buchwald, Tobias Girschick, Eibe Frank, Stefan Kramer |
| 2010 | DIS | Equation Discovery for Model Identification in Respiratory Mechanics of the Mechanically Ventilated Human Lung. | Steven Ganzert, Josef Guttmann, Daniel Steinmann, Stefan Kramer |
| 2010 | DIS | Mining Class-Correlated Patterns for Sequence Labeling. | Thomas Hopf, Stefan Kramer |
| 2010 | DIS | Integer Linear Programming Models for Constrained Clustering. | Marianne Mueller, Stefan Kramer |
| 2010 | DIS | Adapted Transfer of Distance Measures for Quantitative Structure-Activity Relationships. | Ulrich Rckert, Tobias Girschick, Fabian Buchwald, Stefan Kramer |
| 2010 | ILP | A Numerical Refinement Operator Based on Multi-Instance Learning. | rick Alphonse, Tobias Girschick, Fabian Buchwald, Stefan Kramer |
| 2009 | AIME | Prediction of Mechanical Lung Parameters Using Gaussian Process Models. | Steven Ganzert, Stefan Kramer, Knut Mller, Daniel Steinmann, Josef Guttmann |
| 2009 | AIME | Data-Efficient Information-Theoretic Test Selection. | Marianne Mueller, Rmer Rosales, Harald Steck, Sriram Krishnan, Bharat Rao, Stefan Kramer |
| 2009 | ILP | Finding Relational Associations in HIV Resistance Mutation Data. | Lothar Richter, Regina Augustin, Stefan Kramer |
| 2009 | IDA | Subgroup Discovery for Test Selection: A Novel Approach and Its Application to Breast Cancer Diagnosis. | Marianne Mueller, Rmer Rosales, Harald Steck, Sriram Krishnan, Bharat Rao, Stefan Kramer |
| 2009 | KDD | Large-scale graph mining using backbone refinement classes. | Andreas Maunz, Christoph Helma, Stefan Kramer |
| 2008 | EDBT | An inductive database and query language in the relational model. | Lothar Richter, Jrg Wicker, Kristina Kessler, Stefan Kramer |
| 2008 | ICDM | Interpreting PET Scans by Structured Patient Data: A Data Mining Case Study in Dementia Research. | Andreas Hapfelmeier, Jana Schmidt, Marianne Mueller, Stefan Kramer, Robert Perneczky, Alexander Kurz, Alexander Drzezga |
| 2006 | BIBE | Leveraging Chemical Background Knowledge for the Prediction of Growth Inhibition. | Lothar Richter, Stefan Hechtl, Stefan Kramer |
| 2006 | ICML | A statistical approach to rule learning. | Ulrich Rckert, Stefan Kramer |
| 2006 | ILP | Inductive Logic Programming for Gene Regulation Prediction. | Sebastian Frhler, Stefan Kramer |
| 2006 | ILP | Margin-Based First-Order Rule Learning. | Ulrich Rckert, Stefan Kramer |
| 2006 | PSB | Learning a Predictive Model for Growth Inhibition from the NCI DTP Human Tumor Cell Line Screening Data: Does Gene Expression Make a Difference? | Lothar Richter, Ulrich Rckert, Stefan Kramer |
| 2005 | ECCB | Analyzing microarray data using quantitative association rules. | Elisabeth Georgii, Lothar Richter, Ulrich Rckert, Stefan Kramer |
| 2005 | ICDM | Fast Frequent String Mining Using Suffix Arrays. | Johannes Fischer, Volker Heun, Stefan Kramer |
| 2004 | ICDM | Quantitative Association Rules Based on Half-Spaces: An Optimization Approach. | Ulrich Rckert, Lothar Richter, Stefan Kramer |
| 2004 | ICML | Ensembles of nested dichotomies for multi-class problems. | Eibe Frank, Stefan Kramer |
| 2004 | ICML | Towards tight bounds for rule learning. | Ulrich Rckert, Stefan Kramer |
| 2004 | SAC | Frequent free tree discovery in graph data. | Ulrich Rckert, Stefan Kramer |
| 2003 | CaiSE | Metamodel-Compliance Checking of Requirements in a Semiformal Representation. | Hermann Kaindl, Stefan Kramer, Mario Hailing, Vahan Harput |
| 2003 | ICML | Stochastic Local Search in k-Term DNF Learning. | Ulrich Rckert, Stefan Kramer |
| 2003 | PSB | Towards Discovering Structural Signatures of Protein Folds Based on Logical Hidden Markov Models. | Kristian Kersting, Tapani Raiko, Stefan Kramer, Luc De Raedt |
| 2002 | ICML | Transformation-Based Regression. | Bjrn Bringmann, Stefan Kramer, Friedrich Neubarth, Hannes Pirker, Gerhard Widmer |
| 2001 | ICML | Feature Construction with Version Spaces for Biochemical Applications. | Stefan Kramer, Luc De Raedt |
| 2001 | IJCAI | The Levelwise Version Space Algorithm and its Application to Molecular Fragment Finding. | Luc De Raedt, Stefan Kramer |
| 2001 | ILP | Demand-Driven Construction of Structural Features in ILP. | Stefan Kramer |
| 2001 | KDD | Molecular feature mining in HIV data. | Stefan Kramer, Luc De Raedt, Christoph Helma |
| 2000 | ECAI | Learning to Use Operational Advice. | Johannes Frnkranz, Bernhard Pfahringer, Hermann Kaindl, Stefan Kramer |
| 2000 | ILP | Bottom-Up Propositionalization. | Stefan Kramer, Eibe Frank |
| 2000 | ISMIS | Prediction of Ordinal Classes Using Regression Trees. | Stefan Kramer, Gerhard Widmer, Bernhard Pfahringer, Michael de Groeve |
| 1999 | ILP | Experiments in Predicting Biodegradability. | Saso Dzeroski, Hendrik Blockeel, Boris Kompare, Stefan Kramer, Bernhard Pfahringer, Wim Van Laer |
| 1998 | ILP | Stochastic Propositionalization of Non-determinate Background Knowledge. | Stefan Kramer, Bernhard Pfahringer, Christoph Helma |
| 1997 | IJCAI | Can We Benefit from Metrics in KBS Development? | Stefan Kramer, Hermann Kaindl, Stefan Schlee |
| 1997 | ICSE | Integrating Forward and Reverse Object-Oriented Software Engineering. | Christoph Welsch, Alexander Schalk, Stefan Kramer |
| 1997 | KDD | Mining for Causes of Cancer: Machine Learning Experiments at Various Levels of Detail. | Stefan Kramer, Bernhard Pfahringer, Christoph Helma |
| 1996 | AAAI | Structural Regression Trees. | Stefan Kramer |
| 1996 | KDD | Efficient Search for Strong Partial Determinations. | Stefan Kramer, Bernhard Pfahringer |
| 1995 | KDD | Compression-Based Evaluation of Partial Determinations. | Bernhard Pfahringer, Stefan Kramer |