Publications

Marquetand P. Recent Progress in Electro- and Photocatalyst Discovery with Machine Learning. Chemical Reviews. 2022 Nov 9;122(21):15996-15997. doi: 10.1021/acs.chemrev.2c00703

Oettershagen L, Kriege NM, Jordan C, Mutzel P. A Temporal Graphlet Kernel for Classifying Dissemination in Evolving Networks. arXiv.org. 2022 Sep 12. doi: https://doi.org/10.48550/arXiv.2209.07332

Bause F, Schubert E, Kriege NM. EmbAssi: embedding assignment costs for similarity search in large graph databases. Data Mining and Knowledge Discovery. 2022 Sep;36(5):1728-1755. Epub 2022 Jul 16. doi: 10.1007/s10618-022-00850-3

Meunier A , Grosse-Wentrup M. A mathematical framework for bridging Marr’s levels. 2022. Paper presented at Conference on Cognitive Computational Neuroscience 2022, San Francisco, California, United States. doi: 10.32470/CCN.2022.1191-0

Westermayr J, Gastegger M, Voros D, Panzenboeck L, Joerg F, Gonzalez L et al. Deep learning study of tyrosine reveals that roaming can lead to photodamage. Nature Chemistry. 2022 Aug;14(8):914-919. doi: 10.1038/s41557-022-00950-z

Grohs P, Jentzen A, Salimova D. Deep neural network approximations for solutions of PDEs based on Monte Carlo algorithms. SN Partial Differential Equations and Applications. 2022 Aug;3(4):45. doi: https://doi.org/10.1007/s42985-021-00100-z

Ghosh A, Tschiatschek S, Devlin S, Singla A. Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes. In Rodrigo MM, Matsuda N, Cristea AI, Dimitrova V, editors, Artificial Intelligence in Education: 23rd International Conference, AIED 2022, Durham, UK, July 27–31, 2022, Proceedings, Part I. Cham: Springer. 2022. p. 28-40. (Lecture Notes in Computer Science, Vol. 13355). doi: https://doi.org/10.1007/978-3-031-11644-5_3

Tschiatschek S, Han D. Option Transfer and SMDP Abstraction with Successor Features. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 2022 doi: https://doi.org/10.24963/ijcai.2022/421

Lindner D, Tschiatschek S, Hofmann K, Krause A. Interactively Learning Preference Constraints in Linear Bandits. In Proceedings of the 39th International Conference on Machine Learning: 17-23 July 2022, Baltimore, Maryland, USA. 2022. (Proceedings of Machine Learning Research, Vol. 162).

Kinast A , Braune R , Dörner KF, Rindlerle-Ma S, Weckenborg C. A hybrid metaheuristic solution approach for the cobot assignment and job shop scheduling problem. Journal of Industrial Information Integration. 2022 Jul;28:100350. Epub 2022 Apr 26. doi: 10.1016/j.jii.2022.100350

Dragomir A-G, Van Woensel T, Dörner KF. The pickup and delivery problem with alternative locations and overlapping time windows. Computers & Operations Research. 2022 Jul;143:105758. doi: 10.1016/j.cor.2022.105758

Jalaldoust A, Hlavácková-Schindler K , Plant C. Causal Discovery in Hawkes Processes by Minimum Description Length. In Thirty-Sixth AAAI Conference on Artificial Intelligence; Thirty-Fourth Conference on Innovative Applications of Artificial Intelligence; The Twelveth Symposium on Educational Advances in Artificial Intelligence. Palo Alto, California: AAAI Press. 2022. p. 6978-6987. (Proceedings of the ... National Conference on Artificial Intelligence; No. 6, Vol. 36). doi: 10.48550/arXiv.2206.06124, https://doi.org/10.1609/aaai.v36i6.20656

Tschiatschek S , Knobelsdorf M, Singla A. Equity and Fairness of Bayesian Knowledge Tracing. In Proceedings of the 15th International Conference on Educational Data Mining, EDM 2022. 2022 doi: https://doi.org/10.5281/zenodo.6853012

Bettiol E, Bomze I, Létocart L, Rinaldi F, Traversi E. Mining for diamonds: Matrix generation algorithms for binary quadratically constrained quadratic problems. Computers and Operations Research. 2022 Jun;142:105735. doi: 10.1016/j.cor.2022.105735

Kriege NM. Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited. arXiv.org. 2022 May 22. doi: https://doi.org/10.48550/arXiv.2205.10914

Scherbela M, Reisenhofer R, Gerard L, Marquetand P, Grohs P. Solving the electronic Schrödinger equation for multiple nuclear geometries with weight-sharing deep neural networks. Nature Computational Science. 2022 May 19;2(5):331–341. doi: 10.1038/s43588-022-00228-x

Bomze I , Gabl M, Maggioni F, Pflug G. Two-stage stochastic standard quadratic optimization. European Journal of Operational Research. 2022 May 16;299(1):21-34. doi: 10.1016/j.ejor.2021.10.056

Molnar C, König G, Herbinger J, Freiesleben T, Dandl S, Scholbeck CA et al. General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models. In Holzinger A, Goebel R, Fong R, Moon T, Müller K-R, Samek W, editors, xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers. 1 ed. Cham: Springer. 2022. p. 39-68. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2021 Aug 17. doi: https://doi.org/10.1007/978-3-031-04083-2_4

Oettershagen L, Mutzel P, Kriege NM. Temporal Walk Centrality: Ranking Nodes in Evolving Networks. In Laforest F, Troncy R, editors, WWW 2022 - Proceedings of the ACM Web Conference 2022. New York, NY: Association for Computing Machinery (ACM). 2022. p. 1640-1650 doi: https://doi.org/10.48550/arXiv.2202.03706, 10.1145/3485447.3512210

Bomze I , Gabl M. Uncertainty preferences in robust mixed-integer linear optimization with endogenous uncertainty. SIAM Journal on Optimization. 2022 Mar 24;32(1):292-318. doi: 10.1137/20M1355422