LIANG, Zhouji, WELLMANN, Jan Florian und GHATTAS, Omar, 2023. Derivative-informed Bayesian inference for trainable geological modeling - in modern machine-learning framework. Aachen: Universitätsbibliothek der RWTH Aachen.
Elsevier - Harvard (with titles)Liang, Z., Wellmann, J.F., Ghattas, O., 2023. Derivative-informed Bayesian inference for trainable geological modeling - in modern machine-learning framework. Aachen. RWTH Aachen University, 2023. Universitätsbibliothek der RWTH Aachen, Aachen. https://doi.org/10.18154/RWTH-2024-02206
American Psychological Association 7th editionLiang, Z., Wellmann, J. F., & Ghattas, O. (ca. 2023). Derivative-informed Bayesian inference for trainable geological modeling - in modern machine-learning framework [Universitätsbibliothek der RWTH Aachen; Cd]. In Aachen. RWTH Aachen University, 2023. https://doi.org/10.18154/RWTH-2024-02206
Springer - Basic (author-date)Liang Z, Wellmann JF, Ghattas O (2023) Derivative-informed Bayesian inference for trainable geological modeling - in modern machine-learning framework. Universitätsbibliothek der RWTH Aachen
Juristische Zitierweise (Stüber) (Deutsch)Liang, Zhouji/ Wellmann, Jan Florian/ Ghattas, Omar, Derivative-informed Bayesian inference for trainable geological modeling - in modern machine-learning framework, Aachen 2023.