Publications
Showing entries 181 - 200 out of 245
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 (Author), Meingast S (Author), Alves J (Author), Moeller T (Author), Bomze I (Author). 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 H-C, 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 Sep 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 Sep 16. doi: doi.org/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 (Author), Cebula P (Author), Eder M (Author), Grass A (Author), Hermisson J (Author), Hledik M (Author) 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
Behzadi S, Schelling B, Plant C. ITGH: Information-Theoretic Granger Causal Inference on Heterogeneous Data. In Lauw H, Wong RW, Ntoulas A, Lim EP, Ng SK, Pan S, editors, Advances in Knowledge Discovery and Data Mining. PAKDD 2020. Cham: Springer. 2020. p. 742-755. (Lecture Notes in Computer Science, Vol. 12085).
Plant C, Böhm C. Massively Parallel Random Number Generation. In Wu XT, Jermaine C, Xiong L, Hu XH, Kotevska O, Lu SY, Xu WJ, Aluru S, Zhai CX, Al-Masri E, Chen ZY, Saltz J, editors, 2020 IEEE International Conference on Big Data: Dec 10-Dec 13, 2020, virtual event : proceedings. Piscataway, NJ: IEEE. 2020. p. 413-419 Epub 2020. doi: https://doi.org/10.1109/BigData50022.2020.9377814
Showing entries 181 - 200 out of 245