References in zbMATH (referenced in 1017 articles )

Showing results 1 to 20 of 1017.
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  1. Antonelli, Joseph; Mazumdar, Maitreyi; Bellinger, David; Christiani, David; Wright, Robert; Coull, Brent: Estimating the health effects of environmental mixtures using Bayesian semiparametric regression and sparsity inducing priors (2020)
  2. Bardsley, Johnathan M.; Hansen, Per Christian: MCMC algorithms for computational UQ of nonnegativity constrained linear inverse problems (2020)
  3. Bauder, David; Bodnar, Taras; Parolya, Nestor; Schmid, Wolfgang: Bayesian inference of the multi-period optimal portfolio for an exponential utility (2020)
  4. Bauer, Alexander; Bender, Andreas; Klima, André; Küchenhoff, Helmut: KOALA: a new paradigm for election coverage. An opinion poll-based “now-cast” of probabilities of events in multi-party electoral systems (2020)
  5. Belomestny, D.; Iosipoi, L.; Moulines, E.; Naumov, A.; Samsonov, S.: Variance reduction for Markov chains with application to MCMC (2020)
  6. Borggaard, Jeff; Glatt-Holtz, Nathan; Krometis, Justin: A Bayesian approach to estimating background flows from a passive scalar (2020)
  7. Butler, Troy; Wildey, T.; Yen, Tian Yu: Data-consistent inversion for stochastic input-to-output maps (2020)
  8. Chiu, Sung Nok; Ling, Leevan; McCourt, Michael: On variable and random shape Gaussian interpolations (2020)
  9. Chua, Alvin J. K.: Sampling from manifold-restricted distributions using tangent bundle projections (2020)
  10. Flegg, Jennifer A.; Menon, Shakti N.; Byrne, Helen M.; McElwain, D. L. Sean: A current perspective on wound healing and tumour-induced angiogenesis (2020)
  11. Gugushvili, Shota; van der Meulen, Frank; Schauer, Moritz; Spreij, Peter: Nonparametric Bayesian estimation of a Hölder continuous diffusion coefficient (2020)
  12. Hall, Cameron L.; Porter, Mason A.; Dawkins, Marian S.: Dominance, sharing, and assessment in an iterated hawk-dove game (2020)
  13. Huang, Yifan; Meng, Shengwang: A Bayesian nonparametric model and its application in insurance loss prediction (2020)
  14. Jokhadze, Valeriane; Schmidt, Wolfgang M.: Measuring model risk in financial risk management and pricing (2020)
  15. Kamranfar, H.; Etminan, J.; Chahkandi, M.: Statistical inference for a repairable system subject to shocks: classical vs. Bayesian (2020)
  16. Karasözen, Ezgi; Karasözen, Bülent: Earthquake location methods (2020)
  17. Kellen, David; Klauer, Karl Christoph: Selecting amongst multinomial models: an apologia for normalized maximum likelihood (2020)
  18. Kissas, Georgios; Yang, Yibo; Hwuang, Eileen; Witschey, Walter R.; Detre, John A.; Perdikaris, Paris: Machine learning in cardiovascular flows modeling: predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks (2020)
  19. Kunihama, Tsuyoshi; Li, Zehang Richard; Clark, Samuel J.; Mccormick, Tyler H.: Bayesian factor models for probabilistic cause of death assessment with verbal autopsies (2020)
  20. Lee, Michael D.; Bock, Jason R.; Cushman, Isaiah; Shankle, William R.: An application of multinomial processing tree models and Bayesian methods to understanding memory impairment (2020)

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