| 2025 | CVPR | Joint Out-of-Distribution Filtering and Data Discovery Active Learning. | Sebastian Schmidt, Leonard Schenk, Leo Schwinn, Stephan Gnnemann |
| 2025 | ICCV | GeoDiffusion: A Training-Free Framework for Accurate 3D Geometric Conditioning in Image Generation. | Phillip Mueller, Talip Uenlue, Sebastian Schmidt, Marcel Kollovieh, Jiajie Fan, Stephan Gnnemann, Lars Mikelsons |
| 2025 | ICCV | Prior2former - Evidential Modeling of Mask Transformers for Assumption-Free Open-World Panoptic Segmentation. | Sebastian Schmidt, Julius Krner, Dominik Fuchsgruber, Stefano Gasperini, Federico Tombari, Stephan Gnnemann |
| 2025 | ICLR | Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance. | Dominik Fuchsgruber, Tim Postuvan, Stephan Gnnemann, Simon Geisler |
| 2025 | ICLR | Learning Equivariant Non-Local Electron Density Functionals. | Nicholas Gao, Eike Eberhard, Stephan Gnnemann |
| 2025 | ICLR | MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds. | Leon Hetzel, Johanna Sommer, Bastian Rieck, Fabian J. Theis, Stephan Gnnemann |
| 2025 | ICLR | Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space. | Mohamed Amine Ketata, Nicholas Gao, Johanna Sommer, Tom Wollschlger, Stephan Gnnemann |
| 2025 | ICLR | Flow Matching with Gaussian Process Priors for Probabilistic Time Series Forecasting. | Marcel Kollovieh, Marten Lienen, David Ldke, Leo Schwinn, Stephan Gnnemann |
| 2025 | ICLR | Unlocking Point Processes through Point Set Diffusion. | David Ldke, Enric Rabasseda Ravents, Marcel Kollovieh, Stephan Gnnemann |
| 2025 | ICLR | Exact Certification of (Graph) Neural Networks Against Label Poisoning. | Mahalakshmi Sabanayagam, Lukas Gosch, Stephan Gnnemann, Debarghya Ghoshdastidar |
| 2025 | ICLR | Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning. | Yan Scholten, Stephan Gnnemann |
| 2025 | ICLR | A Probabilistic Perspective on Unlearning and Alignment for Large Language Models. | Yan Scholten, Stephan Gnnemann, Leo Schwinn |
| 2025 | ICML | Uncertainty Estimation for Heterophilic Graphs Through the Lens of Information Theory. | Dominik Fuchsgruber, Tom Wollschlger, Johannes Bordne, Stephan Gnnemann |
| 2025 | ICML | REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective. | Simon Geisler, Tom Wollschlger, M. H. I. Abdalla, Vincent Cohen-Addad, Johannes Gasteiger, Stephan Gnnemann |
| 2025 | ICML | Efficient Time Series Processing for Transformers and State-Space Models through Token Merging. | Leon Gtz, Marcel Kollovieh, Stephan Gnnemann, Leo Schwinn |
| 2025 | ICML | UnHiPPO: Uncertainty-aware Initialization for State Space Models. | Marten Lienen, Abdullah Saydemir, Stephan Gnnemann |
| 2025 | ICML | Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold Interpolation. | Alessandro Palma, Sergei Rybakov, Leon Hetzel, Stephan Gnnemann, Fabian J. Theis |
| 2025 | ICML | Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting. | Jan Schuchardt, Mina Dalirrooyfard, Jed Guzelkabaagac, Anderson Schneider, Yuriy Nevmyvaka, Stephan Gnnemann |
| 2025 | ICML | The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence. | Tom Wollschlger, Jannes Elstner, Simon Geisler, Vincent Cohen-Addad, Stephan Gnnemann, Johannes Gasteiger |
| 2025 | WACV | Finding Dino: A Plug-and-Play Framework for Zero-Shot Detection of Out-of-Distribution Objects Using Prototypes. | Poulami Sinhamahapatra, Franziska Schwaiger, Shirsha Bose, Huiyu Wang, Karsten Roscher, Stephan Gnnemann |
| 2024 | CVPR | Understanding ReLU Network Robustness Through Test Set Certification Performance. | Nicola Franco, Jeanette Miriam Lorenz, Karsten Roscher, Stephan Gnnemann |
| 2024 | CVPR | Towards Engineered Safe AI with Modular Concept Models. | Lena Heidemann, Iwo Kurzidem, Maureen Monnet, Karsten Roscher, Stephan Gnnemann |
| 2024 | ICLR | From Zero to Turbulence: Generative Modeling for 3D Flow Simulation. | Marten Lienen, David Ldke, Jan Hansen-Palmus, Stephan Gnnemann |
| 2024 | ICML | Uncertainty for Active Learning on Graphs. | Dominik Fuchsgruber, Tom Wollschlger, Bertrand Charpentier, Antonio Oroz, Stephan Gnnemann |
| 2024 | ICML | Expressivity and Generalization: Fragment-Biases for Molecular GNNs. | Tom Wollschlger, Niklas Kemper, Leon Hetzel, Johanna Sommer, Stephan Gnnemann |
| 2024 | IJCAI | Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry (Extended Abstract). | Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou, Bernd Bischl, Stephan Gnnemann, David Rgamer |
| 2024 | IROS | Deep Sensor Fusion with Constraint Safety Bounds for High Precision Localization. | Sebastian Schmidt, Ludwig Stumpp, Diego Valverde, Stephan Gnnemann |
| 2024 | QCE | Certifiably Robust Encoding Schemes. | Aman Saxena, Tom Wollschlger, Nicola Franco, Jeanette Miriam Lorenz, Stephan Gnnemann |
| 2024 | QCE | Discrete Randomized Smoothing Meets Quantum Computing. | Tom Wollschlger, Aman Saxena, Nicola Franco, Jeanette Miriam Lorenz, Stephan Gnnemann |
| 2024 | UAI | Guaranteeing Robustness Against Real-World Perturbations In Time Series Classification Using Conformalized Randomized Smoothing. | Nicola Franco, Jakob Spiegelberg, Jeanette Miriam Lorenz, Stephan Gnnemann |
| 2023 | BMVC | Stream-based Active Learning by Exploiting Temporal Properties in Perception with Temporal Predicted Loss. | Sebastian Schmidt, Stephan Gnnemann |
| 2023 | CAIN | Enabling Machine Learning in Software Architecture Frameworks. | Armin Moin, Atta Badii, Stephan Gnnemann, Moharram Challenger |
| 2023 | CoRL | Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning. | Jianxiang Feng, Jongseok Lee, Simon Geisler, Stephan Gnnemann, Rudolph Triebel |
| 2023 | ICLR | Sampling-free Inference for Ab-Initio Potential Energy Surface Networks. | Nicholas Gao, Stephan Gnnemann |
| 2023 | ICLR | Revisiting Robustness in Graph Machine Learning. | Lukas Gosch, Daniel Sturm, Simon Geisler, Stephan Gnnemann |
| 2023 | ICLR | Unveiling the sampling density in non-uniform geometric graphs. | Raffaele Paolino, Aleksandar Bojchevski, Stephan Gnnemann, Gitta Kutyniok, Ron Levie |
| 2023 | ICLR | Localized Randomized Smoothing for Collective Robustness Certification. | Jan Schuchardt, Tom Wollschlger, Aleksandar Bojchevski, Stephan Gnnemann |
| 2023 | ICML | Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion. | Marin Bilos, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, Stephan Gnnemann |
| 2023 | ICML | Generalizing Neural Wave Functions. | Nicholas Gao, Stephan Gnnemann |
| 2023 | ICML | Transformers Meet Directed Graphs. | Simon Geisler, Yujia Li, Daniel J. Mankowitz, Ali Taylan Cemgil, Stephan Gnnemann, Cosmin Paduraru |
| 2023 | ICML | Ewald-based Long-Range Message Passing for Molecular Graphs. | Arthur Kosmala, Johannes Gasteiger, Nicholas Gao, Stephan Gnnemann |
| 2023 | ICML | Uncertainty Estimation for Molecules: Desiderata and Methods. | Tom Wollschlger, Nicholas Gao, Bertrand Charpentier, Mohamed Amine Ketata, Stephan Gnnemann |
| 2023 | QCE | Efficient MILP Decomposition in Quantum Computing for ReLU Network Robustness. | Nicola Franco, Tom Wollschlger, Benedikt Poggel, Stephan Gnnemann, Jeanette Miriam Lorenz |
| 2022 | AAAI | Domain Reconstruction for UWB Car Key Localization Using Generative Adversarial Networks. | Aleksei Kuvshinov, Daniel Knobloch, Daniel Klzer, Elen Vardanyan, Stephan Gnnemann |
| 2022 | AAAI | Is it all a cluster game? - Exploring Out-of-Distribution Detection based on Clustering in the Embedding Space. | Poulami Sinhamahapatra, Rajat Koner, Karsten Roscher, Stephan Gnnemann |
| 2022 | COMPSAC | Supporting AI Engineering on the IoT Edge through Model-Driven TinyML. | Armin Moin, Moharram Challenger, Atta Badii, Stephan Gnnemann |
| 2022 | CVPR | Understanding the Role of Weather Data for Earth Surface Forecasting using a ConvLSTM-based Model. | Codrut-Andrei Diaconu, Sudipan Saha, Stephan Gnnemann, Xiao Xiang Zhu |
| 2022 | GI | Towards Model-Driven Engineering for Quantum AI. | Armin Moin, Moharram Challenger, Atta Badii, Stephan Gnnemann |
| 2022 | ICLR | Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions. | Bertrand Charpentier, Oliver Borchert, Daniel Zgner, Simon Geisler, Stephan Gnnemann |
| 2022 | ICLR | Differentiable DAG Sampling. | Bertrand Charpentier, Simon Kibler, Stephan Gnnemann |
| 2022 | ICLR | Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions. | Nicholas Gao, Stephan Gnnemann |
| 2022 | ICLR | Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness. | Simon Geisler, Johanna Sommer, Jan Schuchardt, Aleksandar Bojchevski, Stephan Gnnemann |
| 2022 | ICLR | Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks. | Marten Lienen, Stephan Gnnemann |
| 2022 | ICLR | End-to-End Learning of Probabilistic Hierarchies on Graphs. | Daniel Zgner, Bertrand Charpentier, Morgane Ayle, Sascha Geringer, Stephan Gnnemann |
| 2022 | ICML | Winning the Lottery Ahead of Time: Efficient Early Network Pruning. | John Rachwan, Daniel Zgner, Bertrand Charpentier, Simon Geisler, Morgane Ayle, Stephan Gnnemann |
| 2022 | ICML | 3D Infomax improves GNNs for Molecular Property Prediction. | Hannes Strk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan Gnnemann, Pietro Li |
| 2022 | ICML | Intriguing Properties of Input-Dependent Randomized Smoothing. | Peter Skenk, Aleksei Kuvshinov, Stephan Gnnemann |
| 2022 | ICMLA | Safe Robot Navigation Using Constrained Hierarchical Reinforcement Learning. | Felippe Schmoeller Roza, Hassan Rasheed, Karsten Roscher, Xiangyu Ning, Stephan Gnnemann |
| 2022 | ICSE | ML-Quadrat & DriotData: A Model-Driven Engineering Tool and a Low-Code Platform for Smart IoT Services. | Armin Moin, Andrei Mituca, Moharram Challenger, Atta Badii, Stephan Gnnemann |
| 2022 | MODELS | MDE for machine learning-enabled software systems: a case study and comparison of MontiAnna & ML-Quadrat. | Jrg Christian Kirchhof, Evgeny Kusmenko, Jonas Ritz, Bernhard Rumpe, Armin Moin, Atta Badii, Stephan Gnnemann, Moharram Challenger |
| 2022 | QCE | Quantum Robustness Verification: A Hybrid Quantum-Classical Neural Network Certification Algorithm. | Nicola Franco, Tom Wollschlger, Nicholas Gao, Jeanette Miriam Lorenz, Stephan Gnnemann |
| 2021 | AISTATS | Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions. | Yihan Wu, Aleksandar Bojchevski, Aleksei Kuvshinov, Stephan Gnnemann |
| 2021 | BMVC | OODformer: Out-Of-Distribution Detection Transformer. | Rajat Koner, Poulami Sinhamahapatra, Karsten Roscher, Stephan Gnnemann, Volker Tresp |
| 2021 | ICLR | Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks. | Jan Schuchardt, Aleksandar Bojchevski, Johannes Klicpera, Stephan Gnnemann |
| 2021 | ICLR | Language-Agnostic Representation Learning of Source Code from Structure and Context. | Daniel Zgner, Tobias Kirschstein, Michele Catasta, Jure Leskovec, Stephan Gnnemann |
| 2021 | ICML | Scalable Normalizing Flows for Permutation Invariant Densities. | Marin Bilos, Stephan Gnnemann |
| 2021 | ICML | Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More. | Johannes Klicpera, Marten Lienen, Stephan Gnnemann |
| 2021 | ICML | Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable? | Anna-Kathrin Kopetzki, Bertrand Charpentier, Daniel Zgner, Sandhya Giri, Stephan Gnnemann |
| 2021 | IJCAI | Domain Shifts in Reinforcement Learning: Identifying Disturbances in Environments. | Tom Haider, Felippe Schmoeller Roza, Dirk Eilers, Karsten Roscher, Stephan Gnnemann |
| 2021 | IJCAI | Neural Temporal Point Processes: A Review. | Oleksandr Shchur, Ali Caner Trkmen, Tim Januschowski, Stephan Gnnemann |
| 2021 | SSDBM | In-Database Machine Learning with SQL on GPUs. | Maximilian E. Schle, Harald Lang, Maximilian Springer, Alfons Kemper, Thomas Neumann, Stephan Gnnemann |
| 2020 | ALENEX | Group Centrality Maximization for Large-scale Graphs. | Eugenio Angriman, Alexander van der Grinten, Aleksandar Bojchevski, Daniel Zgner, Stephan Gnnemann, Henning Meyerhenke |
| 2020 | ECCV | Assessing Box Merging Strategies and Uncertainty Estimation Methods in Multimodel Object Detection. | Felippe Schmoeller Roza, Maximilian Henne, Karsten Roscher, Stephan Gnnemann |
| 2020 | ICLR | Directional Message Passing for Molecular Graphs. | Johannes Klicpera, Janek Gro, Stephan Gnnemann |
| 2020 | ICLR | Continual Learning with Bayesian Neural Networks for Non-Stationary Data. | Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick van der Smagt, Stephan Gnnemann |
| 2020 | ICLR | Intensity-Free Learning of Temporal Point Processes. | Oleksandr Shchur, Marin Bilos, Stephan Gnnemann |
| 2020 | ICML | Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More. | Aleksandar Bojchevski, Johannes Klicpera, Stephan Gnnemann |
| 2020 | KDD | Scaling Graph Neural Networks with Approximate PageRank. | Aleksandar Bojchevski, Johannes Klicpera, Bryan Perozzi, Amol Kapoor, Martin Blais, Benedek Rzemberczki, Michal Lukasik, Stephan Gnnemann |
| 2020 | KDD | Certifiable Robustness of Graph Convolutional Networks under Structure Perturbations. | Daniel Zgner, Stephan Gnnemann |
| 2020 | MODELS | From things' modeling language (ThingML) to things' machine learning (ThingML2). | Armin Moin, Stephan Rssler, Marouane Sayih, Stephan Gnnemann |
| 2019 | AAAI | Multi-Source Neural Variational Inference. | Richard Kurle, Stephan Gnnemann, Patrick van der Smagt |
| 2019 | BTW | In-Database Machine Learning: Gradient Descent and Tensor Algebra for Main Memory Database Systems. | Maximilian E. Schle, Frdric Simonis, Thomas Heyenbrock, Alfons Kemper, Stephan Gnnemann, Thomas Neumann |
| 2019 | DAC | Learning Temporal Specifications from Imperfect Traces Using Bayesian Inference. | Artur Mrowca, Martin Nocker, Sebastian Steinhorst, Stephan Gnnemann |
| 2019 | EDBT | ML2SQL - Compiling a Declarative Machine Learning Language to SQL and Python. | Maximilian E. Schle, Matthias Bungeroth, Dimitri Vorona, Alfons Kemper, Stephan Gnnemann, Thomas Neumann |
| 2019 | EDBT | The Power of SQL Lambda Functions. | Maximilian E. Schle, Dimitri Vorona, Linnea Passing, Harald Lang, Alfons Kemper, Stephan Gnnemann, Thomas Neumann |
| 2019 | GI | Adversarial Attacks on Graph Neural Networks. | Daniel Zgner, Amir Akbarnejad, Stephan Gnnemann |
| 2019 | ICLR | Predict then Propagate: Graph Neural Networks meet Personalized PageRank. | Johannes Klicpera, Aleksandar Bojchevski, Stephan Gnnemann |
| 2019 | ICLR | Adversarial Attacks on Graph Neural Networks via Meta Learning. | Daniel Zgner, Stephan Gnnemann |
| 2019 | ICML | Adversarial Attacks on Node Embeddings via Graph Poisoning. | Aleksandar Bojchevski, Stephan Gnnemann |
| 2019 | IJCAI | Adversarial Attacks on Neural Networks for Graph Data. | Daniel Zgner, Amir Akbarnejad, Stephan Gnnemann |
| 2019 | KDD | Certifiable Robustness and Robust Training for Graph Convolutional Networks. | Daniel Zgner, Stephan Gnnemann |
| 2019 | WWW | GhostLink: Latent Network Inference for Influence-aware Recommendation. | Subhabrata Mukherjee, Stephan Gnnemann |
| 2019 | SIGMOD | MLearn: A Declarative Machine Learning Language for Database Systems. | Maximilian E. Schle, Matthias Bungeroth, Alfons Kemper, Stephan Gnnemann, Thomas Neumann |
| 2018 | AAAI | Bayesian Robust Attributed Graph Clustering: Joint Learning of Partial Anomalies and Group Structure. | Aleksandar Bojchevski, Stephan Gnnemann |
| 2018 | ICDM | Anomaly Detection in Car-Booking Graphs. | Oleksandr Shchur, Aleksandar Bojchevski, Mohamed Farghal, Stephan Gnnemann, Yusuf Saber |
| 2018 | ICLR | Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking. | Aleksandar Bojchevski, Stephan Gnnemann |
| 2018 | ICML | NetGAN: Generating Graphs via Random Walks. | Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zgner, Stephan Gnnemann |
| 2018 | KDD | Adversarial Attacks on Neural Networks for Graph Data. | Daniel Zgner, Amir Akbarnejad, Stephan Gnnemann |
| 2018 | MODELS | ThingML+: Augmenting Model-Driven Software Engineering for the Internet of Things with Machine Learning. | Armin Moin, Stephan Rssler, Stephan Gnnemann |
| 2018 | SDM | Making Kernel Density Estimation Robust towards Missing Values in Highly Incomplete Multivariate Data without Imputation. | Richard Leibrandt, Stephan Gnnemann |
| 2018 | SDM | An LSTM Approach to Patent Classification based on Fixed Hierarchy Vectors. | Marawan Shalaby, Jan Stutzki, Matthias Schubert, Stephan Gnnemann |
| 2018 | SISAP | Intrinsic Degree: An Estimator of the Local Growth Rate in Graphs. | Lorenzo von Ritter, Michael E. Houle, Stephan Gnnemann |
| 2017 | BTW | Efficient Batched Distance and Centrality Computation in Unweighted and Weighted Graphs. | Manuel Then, Stephan Gnnemann, Alfons Kemper, Thomas Neumann |
| 2017 | EDBT | SQL- and Operator-centric Data Analytics in Relational Main-Memory Databases. | Linnea Passing, Manuel Then, Nina C. Hubig, Harald Lang, Michael Schreier, Stephan Gnnemann, Alfons Kemper, Thomas Neumann |
| 2017 | KDD | Robust Spectral Clustering for Noisy Data: Modeling Sparse Corruptions Improves Latent Embeddings. | Aleksandar Bojchevski, Yves Matkovic, Stephan Gnnemann |
| 2017 | SDM | The Power of Certainty: A Dirichlet-Multinomial Model for Belief Propagation. | Dhivya Eswaran, Stephan Gnnemann, Christos Faloutsos |
| 2016 | ICDM | Hyperbolae are No Hyperbole: Modelling Communities That are Not Cliques. | Saskia Metzler, Stephan Gnnemann, Pauli Miettinen |
| 2016 | ICDM | EdgeCentric: Anomaly Detection in Edge-Attributed Networks. | Neil Shah, Alex Beutel, Bryan Hooi, Leman Akoglu, Stephan Gnnemann, Disha Makhija, Mohit Kumar, Christos Faloutsos |
| 2016 | KDD | Continuous Experience-aware Language Model. | Subhabrata Mukherjee, Stephan Gnnemann, Gerhard Weikum |
| 2016 | SDM | BIRDNEST: Bayesian Inference for Ratings-Fraud Detection. | Bryan Hooi, Neil Shah, Alex Beutel, Stephan Gnnemann, Leman Akoglu, Mohit Kumar, Disha Makhija, Christos Faloutsos |
| 2015 | AISTATS | Preferential Attachment in Graphs with Affinities. | Jay Lee, Manzil Zaheer, Stephan Gnnemann, Alexander J. Smola |
| 2015 | ICDM | Automatic Taxonomy Extraction from Bipartite Graphs. | Tobias Ktter, Stephan Gnnemann, Michael R. Berthold, Christos Faloutsos |
| 2015 | WWW | Extracting Taxonomies from Bipartite Graphs. | Tobias Ktter, Stephan Gnnemann, Christos Faloutsos, Michael R. Berthold |
| 2014 | KDD | SMVC: semi-supervised multi-view clustering in subspace projections. | Stephan Gnnemann, Ines Frber, Matthias Sebastian Rdiger, Thomas Seidl |
| 2014 | KDD | Detecting anomalies in dynamic rating data: a robust probabilistic model for rating evolution. | Stephan Gnnemann, Nikou Gnnemann, Christos Faloutsos |
| 2014 | PAKDD | Com2: Fast Automatic Discovery of Temporal ('Comet') Communities. | Miguel Araujo, Spiros Papadimitriou, Stephan Gnnemann, Christos Faloutsos, Prithwish Basu, Ananthram Swami, Evangelos E. Papalexakis, Danai Koutra |
| 2014 | PAKDD | Fault-Tolerant Concept Detection in Information Networks. | Tobias Ktter, Stephan Gnnemann, Michael R. Berthold, Christos Faloutsos |
| 2014 | WWW | Robust multivariate autoregression for anomaly detection in dynamic product ratings. | Nikou Gnnemann, Stephan Gnnemann, Christos Faloutsos |
| 2013 | BTW | Subspace Clustering for Complex Data. | Stephan Gnnemann |
| 2013 | ICDM | Mixed Membership Subspace Clustering. | Stephan Gnnemann, Christos Faloutsos |
| 2013 | ICDM | Spectral Subspace Clustering for Graphs with Feature Vectors. | Stephan Gnnemann, Ines Frber, Sebastian Raubach, Thomas Seidl |
| 2013 | ICDM | An Evaluation Framework for Temporal Subspace Clustering Approaches. | Hardy Kremer, Stephan Gnnemann, Arne Held, Thomas Seidl |
| 2013 | KDD | Finding contexts of social influence in online social networks. | Jennifer H. Nguyen, Bo Hu, Stephan Gnnemann, Martin Ester |
| 2013 | PAKDD | Efficient Mining of Combined Subspace and Subgraph Clusters in Graphs with Feature Vectors. | Stephan Gnnemann, Brigitte Boden, Ines Frber, Thomas Seidl |
| 2013 | SSDBM | RMiCS: a robust approach for mining coherent subgraphs in edge-labeled multi-layer graphs. | Brigitte Boden, Stephan Gnnemann, Holger Hoffmann, Thomas Seidl |
| 2013 | SSDBM | Nesting the earth mover's distance for effective cluster tracing. | Hardy Kremer, Stephan Gnnemann, Simon Wollwage, Thomas Seidl |
| 2012 | CIKM | Tracing clusters in evolving graphs with node attributes. | Brigitte Boden, Stephan Gnnemann, Thomas Seidl |
| 2012 | ICDE | Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data. | Emmanuel Mller, Stephan Gnnemann, Ines Frber, Thomas Seidl |
| 2012 | ICDM | Assessing the Significance of Data Mining Results on Graphs with Feature Vectors. | Stephan Gnnemann, Phuong Dao, Mohsen Jamali, Martin Ester |
| 2012 | ICDM | A Subspace Clustering Extension for the KNIME Data Mining Framework. | Stephan Gnnemann, Hardy Kremer, Richard Musiol, Roman Haag, Thomas Seidl |
| 2012 | ICDM | Effective and Robust Mining of Temporal Subspace Clusters. | Hardy Kremer, Stephan Gnnemann, Arne Held, Thomas Seidl |
| 2012 | KDD | Mining coherent subgraphs in multi-layer graphs with edge labels. | Brigitte Boden, Stephan Gnnemann, Holger Hoffmann, Thomas Seidl |
| 2012 | KDD | Multi-view clustering using mixture models in subspace projections. | Stephan Gnnemann, Ines Frber, Thomas Seidl |
| 2012 | KDD | Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the data. | Stephan Gnnemann, Ines Frber, Kittipat Virochsiri, Thomas Seidl |
| 2012 | PAKDD | Mining of Temporal Coherent Subspace Clusters in Multivariate Time Series Databases. | Hardy Kremer, Stephan Gnnemann, Arne Held, Thomas Seidl |
| 2012 | SSDBM | Substructure Clustering: A Novel Mining Paradigm for Arbitrary Data Types. | Stephan Gnnemann, Brigitte Boden, Thomas Seidl |
| 2011 | BTW | A Framework for Evaluation and Exploration of Clustering Algorithms in Subspaces of High Dimensional Databases. | Emmanuel Mller, Ira Assent, Stephan Gnnemann, Patrick Gerwert, Matthias Hannen, Timm Jansen, Thomas Seidl |
| 2011 | CIKM | External evaluation measures for subspace clustering. | Stephan Gnnemann, Ines Frber, Emmanuel Mller, Ira Assent, Thomas Seidl |
| 2011 | CIKM | Scalable density-based subspace clustering. | Emmanuel Mller, Ira Assent, Stephan Gnnemann, Thomas Seidl |
| 2011 | EDBT | Subspace clustering for indexing high dimensional data: a main memory index based on local reductions and individual multi-representations. | Stephan Gnnemann, Hardy Kremer, Dominik Lenhard, Thomas Seidl |
| 2011 | ICDM | Flexible Fault Tolerant Subspace Clustering for Data with Missing Values. | Stephan Gnnemann, Emmanuel Mller, Sebastian Raubach, Thomas Seidl |
| 2011 | PAKDD | Tracing Evolving Clusters by Subspace and Value Similarity. | Stephan Gnnemann, Hardy Kremer, Charlotte Laufktter, Thomas Seidl |
| 2011 | SSDBM | Efficient Processing of Multiple DTW Queries in Time Series Databases. | Hardy Kremer, Stephan Gnnemann, Anca Maria Ivanescu, Ira Assent, Thomas Seidl |
| 2010 | EDBT | Pattern detector: fast detection of suspicious stream patterns for immediate reaction. | Ira Assent, Hardy Kremer, Stephan Gnnemann, Thomas Seidl |
| 2010 | ICDM | Subspace Clustering Meets Dense Subgraph Mining: A Synthesis of Two Paradigms. | Stephan Gnnemann, Ines Frber, Brigitte Boden, Thomas Seidl |
| 2010 | ICDM | MCExplorer: Interactive Exploration of Multiple (Subspace) Clustering Solutions. | Stephan Gnnemann, Hardy Kremer, Ines Frber, Thomas Seidl |
| 2010 | ICDM | Detecting Climate Change in Multivariate Time Series Data by Novel Clustering and Cluster Tracing Techniques. | Hardy Kremer, Stephan Gnnemann, Thomas Seidl |
| 2010 | ICDM | Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data. | Emmanuel Mller, Stephan Gnnemann, Ines Frber, Thomas Seidl |
| 2010 | PAKDD | Subgraph Mining on Directed and Weighted Graphs. | Stephan Gnnemann, Thomas Seidl |
| 2010 | SDM | Subspace Clustering for Uncertain Data. | Stephan Gnnemann, Hardy Kremer, Thomas Seidl |
| 2010 | SSDBM | MC-Tree: Improving Bayesian Anytime Classification. | Philipp Kranen, Stephan Gnnemann, Sergej Fries, Thomas Seidl |
| 2009 | BTW | High-Dimensional Indexing for Multimedia Features. | Ira Assent, Stephan Gnnemann, Hardy Kremer, Thomas Seidl |
| 2009 | CIKM | Detection of orthogonal concepts in subspaces of high dimensional data. | Stephan Gnnemann, Emmanuel Mller, Ines Frber, Thomas Seidl |
| 2009 | ICDM | Relevant Subspace Clustering: Mining the Most Interesting Non-redundant Concepts in High Dimensional Data. | Emmanuel Mller, Ira Assent, Stephan Gnnemann, Ralph Krieger, Thomas Seidl |
| 2009 | SDM | DensEst: Density Estimation for Data Mining in High Dimensional Spaces. | Emmanuel Mller, Ira Assent, Ralph Krieger, Stephan Gnnemann, Thomas Seidl |