Quanten-Monte-Carlo Simulationen. - Wolfgang von der Linden (Physik und Informatik, 1991)

A numerical projection technique for large-scale eigenvalue problems. - Ralf Gamillscheg; Gundolf Haase; Wolfgang von der Linden (Comput. Phys. Commun., 2011)

Polaritonic properties of the Jaynes-Cummings lattice model in two dimensions. - Michael Knap; Enrico Arrigoni; Wolfgang von der Linden (Comput. Phys. Commun., 2011)

Nested sampling, statistical physics and the Potts model. - Manuel J. Pfeifenberger; Michael Rumetshofer; Wolfgang von der Linden (J. Comput. Phys., 2018)

Bayesian Analysis of Femtosecond Pump-Probe Photoelectron-Photoion Coincidence Spectra with Fluctuating Laser Intensities. - Pascal Heim; Michael Rumetshofer; Sascha Ranftl; Bernhard Thaler; Wolfgang E. Ernst; Markus Koch; Wolfgang von der Linden (Entropy, 2019)

Bayesian Uncertainty Quantification with Multi-Fidelity Data and Gaussian Processes for Impedance Cardiography of Aortic Dissection. - Sascha Ranftl; Gian Marco Melito; Vahid Badeli; Alice Reinbacher-Köstinger; Katrin Ellermann; Wolfgang von der Linden (Entropy, 2020)

Bayesian source separation of electrical bioimpedance signals. - Christof Pichler; Sascha Ranftl; Arnulf Heller; Enrico Arrigoni; Wolfgang von der Linden (Biomed. Signal Process. Control., 2021)

Importance of feature engineering and database selection in a machine learning model: A case study on carbon crystal structures. - Franz M. Rohrhofer; Santanu Saha; Simone Di Cataldo; Bernhard C. Geiger; Wolfgang von der Linden; Lilia Boeri (CoRR, 2021)

Cross-Entropy Learning for Aortic Pathology Classification of Artificial Multi-Sensor Impedance Cardiography Signals. - Tobias Spindelböck; Sascha Ranftl; Wolfgang von der Linden (Entropy, 2021)

Stochastic Modeling of Inhomogeneities in the Aortic Wall and Uncertainty Quantification using a Bayesian Encoder-Decoder Surrogate. - Sascha Ranftl; Malte Rolf-Pissarczyk; Gloria Wolkerstorfer; Antonio Pepe 003; Jan Egger; Wolfgang von der Linden; Gerhard A. Holzapfel (CoRR, 2022)