Publications
Showing entries 21 - 40 out of 160
Balazia M, Hlavácková-Schindler K, Sojka P, Plant C. Interpretable Gait Recognition by Granger Causality. arXiv.org. 2022 Jun 14. https://doi.org/10.48550/arXiv.2206.06714
Kriege NM. Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited. arXiv.org. 2022 May 22. 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. https://doi.org/10.1038/s43588-022-00228-x
Ratzenböck S, Obermüller V, Möller T, Alves J, Bomze I. Uncover: Toward Interpretable Models for Detecting New Star Cluster Members. IEEE Transactions on Visualization and Computer Graphics. 2022 May 5;1-1. https://doi.org/10.1109/TVCG.2022.3172560
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. Vol. Lecture Notes in Computer Science. Cham: Springer, Cham. 2022. p. 39-68. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). 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 https://doi.org/10.48550/arXiv.2202.03706, https://doi.org/10.1145/3485447.3512210
Bomze I, Rinaldi F, Zeffiro D. Fast cluster detection in networks by first-order optimization. SIAM Journal on Mathematics of Data Science. 2022 Mar 4;4(1):285-305. https://doi.org/10.1137/21M1408658
Bauer L, Hirsch F, Jones C, Hollander M, Grohs P, Anand A et al. Quantification of Kuramoto Coupling Between Intrinsic Brain Networks Applied to fMRI Data in Major Depressive Disorder. Frontiers in Computational Neuroscience. 2022 Mar 3;16. 729556. https://doi.org/10.3389/fncom.2022.729556
Fröhlich GEA, Gansterer M, Dörner KF. Safe and secure vehicle routing: a survey on minimization of risk exposure. International Transactions in Operational Research. 2022 Mar 1. https://doi.org/10.1111/itor.13130
Kutyniok G, Petersen PC, Raslan M, Schneider R. A theoretical analysis of deep neural networks and parametric PDEs. Constructive Approximation. 2022 Feb;55(1):73-125. https://doi.org/10.1007/s00365-021-09551-4
Elbrächter D, Grohs P, Jentzen A, Schwab C. DNN Expression Rate Analysis of High-dimensional PDEs: Application to Option Pricing. Constructive Approximation. 2022 Feb;55(1):3-71. https://doi.org/10.1007/s00365-021-09541-6
Braune R, Benda F, Dörner KF, Hartl R. A Genetic Programming Learning Approach to Generate Dispatching Rules for Flexible Shop Scheduling Problems. International Journal of Production Economics. 2022 Jan;243. 108342. https://doi.org/10.1016/j.ijpe.2021.108342
Markham A, Das R, Grosse-Wentrup M. A Distance Covariance-based Kernel for Nonlinear Causal Clustering in Heterogeneous Populations. Proceedings of Machine Learning Research (PMLR). 2022;177:542.
Bot RI, Csetnek ER, Sedlmayer M. An accelerated minimax algorithm for convex-concave saddle point problems with nonsmooth coupling function. Computational Optimization and Applications. 2022;1-42. https://doi.org/10.1007/s10589-022-00378-8
Leiber C, Mautz D, Plant C, Böhm C. Automatic Parameter Selection for Non-Redundant Clustering. In Banerjee A, Zhou Z-H, Papalexakis EE, Riondato M, editors, Proceedings of the 2022 SIAM International Conference on Data Mining, SDM 2022, Alexandria, VA, USA, April 28-30, 2022. SIAM. 2022. p. 226-234 https://doi.org/10.1137/1.9781611977172.26
Steinberger L, Leeb H. Conditional predictive inference for stable algorithms. Annals of Statistics. 2022.
Velaj Y, Dolezal D, Ambros R, Plant C, Motschnig R. Designing a Data Science Course for Non-Computer Science Students: Practical Considerations and Findings. In 2022 IEEE Frontiers in Education Conference, FIE 2022. Piscataway, NJ: IEEE. 2022. p. 1-9 https://doi.org/10.1109/FIE56618.2022.9962455
Wu H, Tan S, Li W, Garrard M, Obeng A, Dimmery D et al. Distilling Heterogeneity: From Explanations of Heterogeneous Treatment Effect Models to Interpretable Policies. 2022. Paper presented at 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Washington DC, District of Columbia, United States.
Gerard L, Scherbela M, Marquetand P, Grohs P. Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need?. 2022. Paper presented at Thirty-sixth Conference on Neural Information Processing Systems, New Orleans, United States.
Arbour D, Dimmery D, Mai T, Rao A. Online Balanced Experimental Design. 2022. Paper presented at International Conference on Machine Learning (ICML), Baltimore, United States.