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The problem of assigning probability distributions which objectively reflect the prior information available about experiments is one of the major stumbling blocks in the use of Bayesian methods of data analysis. In this paper the method of Maximum (relative) Entropy (ME) is used to translate the information contained in the known form of the likelihood… (More)

- Peter Dieterich, Rainer Klages, Roland Preuss, Albrecht Schwab
- Proceedings of the National Academy of Sciences…
- 2008

Cell movement--for example, during embryogenesis or tumor metastasis--is a complex dynamical process resulting from an intricate interplay of multiple components of the cellular migration machinery. At first sight, the paths of migrating cells resemble those of thermally driven Brownian particles. However, cell migration is an active biological process… (More)

In the Biomedical Medical Research laboratory in St. Louis Missouri there is an ongoing project to characterize water diffusion in fixed baboon brain using diffusion weighted magnetic resonance imaging as a means of monitoring development throughout gestation. Magnetic resonance images can be made sensitive to diffusion by applying magnetic field gradients… (More)

The spectral properties of the 1-D Hubbard model are obtained from quantum Monte Carlo simulations using the maximum entropy method. The one-particle excitations are characterized by dispersive cosine-like bands. Velocities for spin-and charge excitations are obtained that lead to a conformal charge c = 0:98 0:05 for the largest system simulated (N = 84).… (More)

- W Von Der Linden, R Preuss, W Hanke
- 1995

Bayesian probability theory along with the maximum entropy concept is widely used for inferential problems, particularly to infer dynamic properties of strongly correlated fermion systems from Quantum-Monte-Carlo (QMC) imaginary time data. In current QMC-applications, however, the error-covariance of the QMC data is not treated consistently. Here we present… (More)

- R Preuss, W Hanke, W Von Der Linden
- 2008

On the basis of Quantum-Monte-Carlo results the evolution of the spectral weight A(k, ω) of the two-dimensional Hubbard model is studied from insulating to metallic behavior. As observed in recent photoemission experiments for cuprates, the electronic excitations display essentially doping-independent features: a quasiparticle-like dispersive narrow band of… (More)

- H D Kang, R Preuss, T Schwarz-Selinger, V Dose
- Journal of mass spectrometry : JMS
- 2002

We present a method for the decomposition of the mass spectra of mixed gases using Bayesian probability theory. The method works without any calibration measurement and therefore applies also to the analysis of spectra containing unstable species. For the example of mixtures of three different hydrocarbon gases the algorithm provides concentrations and… (More)

- W Von, Der Linden, R Preuss, V Dose
- 1999

At the heart of Bayesian model comparison lies the so-called prior-predictive value. In the important class of Quantiied-MaxEnt applications analytic approximations are routinely used which often give rise to noise-tting and ringing. We present an improved analytic expression which overcomes these shortcomings. In most interesting real-world problems,… (More)

- R Preuss, V Dose, W Von, Der Linden, D Garching, Germany M Unchen
- 1999

Energy connnement data of large fusion experiments have been analyzed in terms of dimensionless form free scaling functions. Several possible physical scenarios lead to diierent models with a certain number of degrees of freedom. These are used to set up the connnement function as a linear combination of di-mensionless power law terms. Then one has to solve… (More)

- Roland Preuss, Udo von Toussaint
- Entropy
- 2017