2024

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• D. Rudolf, P. Schär. Dimension-independent spectral gap of polar slice sampling. Statistics and Computing 34, (2024)

2023

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• P. Schär. Wasserstein contraction and spectral gap of slice sampling revisited. Electronic Journal of Probability 28, (2023)

• A. Schleitzer, O. Beyersdorff. Classes of Hard Formulas for QBF Resolution. Journal of Artificial Intelligence Research (JAIR), (2023)

• O. Beyersdorff and B. Böhm. Understanding the Relative Strength of QBF CDCL Solvers and QBF Resolution. Logical Methods in Computer Science 19(2), (2023)

• O. Beyersdorff, T. Hoffmann, and L. Spachmann. Proof Complexity of Propositional Model Counting. Proceedings of the 26th International Conference on Theory and Applications of Satisfiability Testing (SAT), (2023)

• B. Böhm and O. Beyersdorff. QCDCL vs QBF Resolution: Further Insights. Proceedings of the 26th International Conference on Theory and Applications of Satisfiability Testing (SAT), (2023) Best student paper award

• P. Schär, M. Habeck, and D. Rudolf. Gibbsian polar slice sampling. Proceedings of the 40th International Conference on Machine Learning (ICML), PMLR 202: 30204-30223, 2023

• M. Blacher, J. Giesen, J. Klaus, C. Staudt, S. Laue, and V. Leis. Efficient and Portable Einstein Summation in SQL. Proceedings of the 49th ACM SIGMOD Conference on Management of Data (SIGMOD), (2023) accepted

• J. Klaus, M. Blacher, A. Goral, P. Lucas, and J. Giesen. A Visual Analytics Workflow for Probabilistic Modeling. Visual Informatics, (2023) accepted

• J. Klaus, M. Blacher, J. Giesen. Compiling Tensor Expressions into Einsum. Proceedings of the 23d International Conference on Computational Science (ICCS), (2023) accepted

• M. Mitterreiter, M. Koch, J. Giesen and S. Laue. Why Capsule Neural Networks Do Not Scale: Challenging the Dynamic Parse-Tree Assumption. Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), (2023) accepted

• O. Beyersdorff, J. Blinkhorn, M. Mahajan, T. Peitl. Hardness Characterisations and Size-width Lower Bounds for QBF Resolution. ACM Transactions on Computational Logic (TOCL) 24(2): 10:1-10:30 (2023)

2022

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• J. Klaus, S. Laue, N. Merk, K. Wiedom, and J. Giesen. Convexity Certificates from Hessians. Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS), (2022) accepted

• D. Eggers, C. Höner zu Siederdissen, and Peter F. Stadler. Accuracy of RNA Structure Prediction Depends on the Pseudoknot Grammar. Proceedings of the 5th Brazilian Symposium on Bioinformatics (BSB), (2022) 20-31

• K. Lawonn, M. Meuschke, P. Eulzer, M. Mitterreiter, J. Giesen, and T. Günther. GRay: Ray Casting for Visualization and Interactive Data Exploration of Gaussian Mixture Models. IEEE Transactions on Visualization and Computer Graphics (IEEE Visualization), (2022) Video and Code Honorable mention award

• B. Böhm, T. Peitl, and O. Beyersdorff. QCDCL with Cube Learning or Pure Literal Elimination - What is Best? Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI), (2022) 1781-1787 Distinguished paper award

• J. Giesen, P. Kahlmeyer, F. Nussbaum and S. Zarriess. Leveraging the Wikipedia Graph for Evaluating Word Embeddings. Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI), (2022) 4136-4142

• B. Böhm, T. Peitl, and O. Beyersdorff. Should Decisions in QCDCL Follow Prefix Order? Proceedings of the 25th International Conference on Theory and Applications of Satisfiability Testing (SAT), (2022) 11:1-11:19

• A. Schleitzer and O. Beyersdorff. Classes of Hard Formulas for QBF Resolution. Proceedings of the 25th International Conference on Theory and Applications of Satisfiability Testing (SAT), (2022) 5:1-5:18 Shortlisted for the best-paper award

• J. Klaus, M. Blacher, J. Giesen, P. Rump and K. Wiedom. Compiling Linear Algebra Expressions into Efficient Code. Proceedings of the 22nd International Conference on Computational Science (ICCS), (2022) 11-17

• E. Georganas, D. Kalamkar, S. Avancha, M. Adelman, D. Aggarwal, C. Anderson, A. Breuer, J. Bruestle, N. Chaudhary, A. Kundu, D. Kutnick, F. Laub, V. Md, S. Misra, R. Mohanty, H. Pabst, B. Retford, B. Ziv, A. Heinecke. Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning and HPC Workloads. Frontiers in Applied Mathematics and Statistics 8:826269