| 2026 | AAAI | Proof Systems for Tensor-based Model Counting. | Olaf Beyersdorff, Joachim Giesen, Andreas Goral, Tim Hoffmann, Kaspar Kasche, Christoph Staudt |
| 2026 | GECCO | Beyond the Training Distribution: Mapping Generalization Boundaries in Neural Program Synthesis. | Henrik Voigt, Michael Habeck, Joachim Giesen |
| 2025 | AAAI | Dimension Reduction for Symbolic Regression. | Paul Kahlmeyer, Markus Fischer, Joachim Giesen |
| 2025 | AAAI | Discovering Symmetries of ODEs by Symbolic Regression. | Paul Kahlmeyer, Niklas Merk, Joachim Giesen |
| 2025 | ASPLOS | Einsum Trees: An Abstraction for Optimizing the Execution of Tensor Expressions. | Alexander Breuer, Mark Blacher, Max Engel, Joachim Giesen, Alexander Heinecke, Julien Klaus, Stefan Remke |
| 2024 | AAAI | Model Counting and Sampling via Semiring Extensions. | Andreas Goral, Joachim Giesen, Mark Blacher, Christoph Staudt, Julien Klaus |
| 2024 | IJCAI | Scaling Up Unbiased Search-based Symbolic Regression. | Paul Kahlmeyer, Joachim Giesen, Michael Habeck, Henrik Voigt |
| 2024 | IJCAI | Convexity Certificates for Symbolic Tensor Expressions. | Paul Gerhardt Rump, Niklas Merk, Julien Klaus, Maurice Wenig, Joachim Giesen |
| 2023 | AAAI | Why Capsule Neural Networks Do Not Scale: Challenging the Dynamic Parse-Tree Assumption. | Matthias Mitterreiter, Marcel Koch, Joachim Giesen, Sren Laue |
| 2023 | ICCS | Compiling Tensor Expressions into Einsum. | Julien Klaus, Mark Blacher, Joachim Giesen |
| 2022 | AAAI | Optimization for Classical Machine Learning Problems on the GPU. | Sren Laue, Mark Blacher, Joachim Giesen |
| 2022 | CIDR | Machine Learning, Linear Algebra, and More: Is SQL All You Need? | Mark Blacher, Joachim Giesen, Sren Laue, Julien Klaus, Viktor Leis |
| 2022 | ICCS | Compiling Linear Algebra Expressions into Efficient Code. | Julien Klaus, Mark Blacher, Joachim Giesen, Paul Gerhardt Rump, Konstantin Wiedom |
| 2022 | IJCAI | Leveraging the Wikipedia Graph for Evaluating Word Embeddings. | Joachim Giesen, Paul Kahlmeyer, Frank Nussbaum, Sina Zarrie |
| 2021 | IJCAI | Method of Moments for Topic Models with Mixed Discrete and Continuous Features. | Joachim Giesen, Paul Kahlmeyer, Sren Laue, Matthias Mitterreiter, Frank Nussbaum, Christoph Staudt, Sina Zarrie |
| 2021 | UAI | Robust principal component analysis for generalized multi-view models. | Frank Nussbaum, Joachim Giesen |
| 2020 | AAAI | GENO - Optimization for Classical Machine Learning Made Fast and Easy. | Sren Laue, Matthias Mitterreiter, Joachim Giesen |
| 2020 | AAAI | A Simple and Efficient Tensor Calculus. | Sren Laue, Matthias Mitterreiter, Joachim Giesen |
| 2020 | IJCAI | Disentangling Direct and Indirect Interactions in Polytomous Item Response Theory Models. | Frank Nussbaum, Joachim Giesen |
| 2020 | VLDB | Fast Entity Resolution With Mock Labels and Sorted Integer Sets. | Mark Blacher, Joachim Giesen, Sren Laue, Julien Klaus, Matthias Mitterreiter |
| 2019 | AAAI | Using Benson's Algorithm for Regularization Parameter Tracking. | Joachim Giesen, Sren Laue, Andreas Lhne, Christopher Schneider |
| 2019 | ALT | Ising Models with Latent Conditional Gaussian Variables. | Frank Nussbaum, Joachim Giesen |
| 2019 | IJCAI | Combining ADMM and the Augmented Lagrangian Method for Efficiently Handling Many Constraints. | Joachim Giesen, Sren Laue |
| 2019 | IJCAI | Efficient Regularization Parameter Selection for Latent Variable Graphical Models via Bi-Level Optimization. | Joachim Giesen, Frank Nussbaum, Christopher Schneider |
| 2015 | ICML | Tracking Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter Domains. | Katharina Blechschmidt, Joachim Giesen, Sren Laue |
| 2014 | AISTATS | Sketching the Support of a Probability Measure. | Joachim Giesen, Sren Laue, Lars Kuehne |
| 2014 | ICML | Robust and Efficient Kernel Hyperparameter Paths with Guarantees. | Joachim Giesen, Sren Laue, Patrick Wieschollek |
| 2012 | ESA | Optimizing over the Growing Spectrahedron. | Joachim Giesen, Martin Jaggi, Sren Laue |
| 2010 | ESA | Approximating Parameterized Convex Optimization Problems. | Joachim Giesen, Martin Jaggi, Sren Laue |
| 2007 | AAIM | Collaborative Ranking: An Aggregation Algorithm for Individuals' Preference Estimation. | Joachim Giesen, Dieter Mitsche, Eva Schuberth |
| 2006 | LATIN | Approximate Sorting. | Joachim Giesen, Eva Schuberth, Milos Stojakovic |
| 2006 | SGP | Probabilistic fingerprints for shapes. | Niloy J. Mitra, Leonidas J. Guibas, Joachim Giesen, Mark Pauly |
| 2005 | FCT | Reconstructing Many Partitions Using Spectral Techniques. | Joachim Giesen, Dieter Mitsche |
| 2005 | ISAAC | Boosting Spectral Partitioning by Sampling and Iteration. | Joachim Giesen, Dieter Mitsche |
| 2005 | SODA | Delaunay triangulations approximate anchor hulls. | Tamal K. Dey, Joachim Giesen, Samrat Goswami |
| 2005 | SGP | Example-Based 3D Scan Completion. | Mark Pauly, Niloy J. Mitra, Joachim Giesen, Markus H. Gross, Leonidas J. Guibas |
| 2005 | WG | Bounding the Misclassification Error in Spectral Partitioning in the Planted Partition Model. | Joachim Giesen, Dieter Mitsche |
| 2003 | SODA | The flow complex: a data structure for geometric modeling. | Joachim Giesen, Matthias John |
| 2003 | STOC | Alpha-shapes and flow shapes are homotopy equivalent. | Tamal K. Dey, Joachim Giesen, Matthias John |
| 2003 | WADS | Shape Segmentation and Matching with Flow Discretization. | Tamal K. Dey, Joachim Giesen, Samrat Goswami |
| 2002 | ICCS | Duality in Disk Induced Flows. | Joachim Giesen, Matthias John |
| 2002 | RE | Requirements Interdependencies and Stakeholders Preferences. | Joachim Giesen, Axel Vlker |
| 2002 | SODA | Shape dimension and approximation from samples. | Tamal K. Dey, Joachim Giesen, Samrat Goswami, Wulue Zhao |
| 2002 | STACS | A New Diagram from Disks in the Plane. | Joachim Giesen, Matthias John |
| 2002 | SIROCCO | Towards a Theory of Peer-to-Peer Computability. | Joachim Giesen, Roger Wattenhofer, Aaron Zollinger |
| 2001 | ICCS | Robustness Issues in Surface Reconstruction. | Tamal K. Dey, Joachim Giesen, Wulue Zhao |