Publications

Kaufman B, Rozgonyi T, Marquetand P, Weinacht T. Coherent Control of Internal Conversion in Strong-Field Molecular Ionization. Physical Review Letters. 2020 Jul 29;125(5):053202. doi: 10.1103/PhysRevLett.125.053202

Molnar C, König G, Herbinger J, Freiesleben T, Dandl S, Scholbeck CA et al.. Pitfalls to Avoid when Interpreting Machine Learning Models. 2020. Paper presented at XXAI: Extending Explainable AI Beyond Deep Models and Classifiers, Wien, Austria. Epub 2020 Jul 8. doi: 10.48550/arXiv.2007.04131

Ratzenboeck S, Meingast S , Alves J , Moeller T , Bomze I. Extended stellar systems in the solar neighborhood IV: Meingast 1: the most massive stellar stream in the solar neighborhood. Astronomy & Astrophysics. 2020 Jul 7;639:A64. doi: 10.1051/0004-6361/202037591

Ratzenboeck S, Meingast S , Alves J , Moeller T , Bomze I. VizieR Online Data Catalog: Extended Meingast 1 source catalogue (Ratzenboeck+, 2020). 2020.

Westermayr J, Gastegger M, Marquetand P. Combining SchNet and SHARC: The SchNarc Machine Learning Approach for Excited-State Dynamics. Journal of Physical Chemistry Letters. 2020 May 21;11(10):3828-3834. doi: 10.1021/acs.jpclett.0c00527

Westermayr J, Faber FA, Christensen AS, von Lilienfeld OA, Marquetand P. Neural networks and kernel ridge regression for excited states dynamics of CH₂NH₂⁺: From single-state to multi-state representations and multi-property machine learning models. Machine Learning: Science and Technology. 2020 May 19;1(2):025009. doi: 10.1088/2632-2153/ab88d0

Liu Y, Horton SL, Yang J, Nunes JPF, Shen X, Wolfe TJA et al. Spectroscopic and Structural Probing of Excited-State Molecular Dynamics with Time-Resolved Photoelectron Spectroscopy and Ultrafast Electron Diffraction. Physical Review X. 2020 Apr 22;10(2):021016. doi: 10.1103/PhysRevX.10.021016

Altinigneli MC, Bauer LGM, Behzadi S, Fritze R, Hlavackova-Schindler K, Leodolter M et al. The Data Mining Group at University of Vienna. Datenbank-Spektrum. 2020 Mar 1;20:71-79. doi: 10.1007/s13222-020-00337-9

Hautsch N, Herrera Leiva R. Multivariate Dynamic Intensity Peaks-Over-Threshold Models. Journal of Applied Econometrics. 2020 Mar;35(2):248-272. doi: 10.1002/jae.2741

Schelling B, Plant C. Dataset-Transformation: Improving Clustering by enhancing the structure with DipScaling and DipTransformation. Knowledge and Information Systems. 2020 Feb;62(2):457-484. doi: 10.1007/s10115-019-01388-5

Fröhler BW, Elberfeld T, Möller T, Hege HC, de Beenhouwer J, Sijbers J et al. Analysis and comparison of algorithms for the tomographic reconstruction of curved fibres. Nondestructive Testing and Evaluation. 2020 Jan 16;35(3):328-341. doi: 10.1080/10589759.2020.1774583

Möller T. Origins. IEEE Computer Graphics & Application . 2020 Jan 7;40(1):14-19. 8951769. doi: 10.1109/MCG.2019.2957689

Sarasola B, Dörner KF. Adaptive large neighborhood search for the vehicle routing problem with synchronization constraints at the delivery location. Networks (New York): an international journal. 2020 Jan;75(1):64-85. Epub 2019 Sept 14. doi: 10.1002/net.21905

Bot RI , Sedlmayer M, Phan TV. A Relaxed Inertial Forward-Backward-Forward Algorithm for Solving Monotone Inclusions with Application to GANs. arXiv.org. 2020. doi: https://arxiv.org/abs/2003.07886

Bomze I, Rinaldi F, Zeffiro D. Active Set Complexity of the Away-Step Frank--Wolfe Algorithm. SIAM Journal on Optimization. 2020;30(3):2470-2500. Epub 2020 Sept 16. doi: 10.1137/19M1309419

Kivaranovic D, Johnson K, Leeb H. Adaptive, distribution-free prediction intervals for deep neural networks. Proceedings of Machine Learning Research. 2020;108:4346-4356.

Plant C, Biedermann S, Böhm C. Data Compression as a Comprehensive Framework for Graph Drawing and Representation Learning. In KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23-27, 2020. ACM. 2020. p. 1212-1222

Miklautz L, Mautz D, Altinigneli MC, Böhm C, Plant C. Deep Embedded Non-Redundant Clustering. Proceedings of the ... National Conference on Artificial Intelligence. 2020;34(04):5174-5181. doi: 10.1609/aaai.v34i04.5961

Beiglböck M, Cebula P, Eder M, Grass A, Hermisson J, Hledik M et al.. EpiMath Austria: COVID-19 Modellierung am Beispiel Österreich 2020.

Altinigneli MC, Miklautz L, Böhm C, Plant C. Hierarchical Quick Shift Guided Recurrent Clustering. In 36th IEEE International Conference on Data Engineering, ICDE 2020, Dallas, TX, USA, April 20-24, 2020. IEEE. 2020. p. 1842-1845