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We present a statistical perspective on boosting. Special emphasis is given to estimating potentially complex parametric or nonparametric models, including generalized linear and additive models as well as regression models for survival…

Methodology · Statistics 2008-12-18 Peter Bühlmann , Torsten Hothorn

We describe some scaling issues that arise when using lattice Boltzmann methods to simulate binary fluid mixtures -- both in the presence and in the absence of colloidal particles. Two types of scaling problem arise: physical and…

Soft Condensed Matter · Physics 2009-11-10 M. E. Cates , J. -C. Desplat , P. Stansell , A. J. Wagner , K. Stratford , R. Adhikari , I. Pagonabarraga

Our aim is to provide an overview of half-saturation constants reported in literature and to explore their consistency with body size. In many ecological models, intake of nutrients by plants and consumption of food by animals is considered…

Quantitative Methods · Quantitative Biology 2014-10-08 Christian Mulder , A. Jan Hendriks

Although power laws of the Zipf type have been used by many workers to fit rank distributions in different fields like in economy, geophysics, genetics, soft-matter, networks etc., these fits usually fail at the tails. Some distributions…

Data Analysis, Statistics and Probability · Physics 2015-10-12 Gerardo G. Naumis , Germinal Cocho

The methods of statistical mechanics are applied to two-dimensional foams under macroscopic agitation. A new variable -- the total cell curvature -- is introduced, which plays the role of energy in conventional statistical thermodynamics.…

Soft Condensed Matter · Physics 2011-11-10 Marc Durand

We introduce in this paper a new four-parameter generalized version of the linear failure rate (LFR) distribution which is called Beta-linear failure rate (BLFR) distribution. The new distribution is quite flexible and can be used…

Methodology · Statistics 2012-12-27 Ali Akbar Jafari , Eisa Mahmoudi

Factor modeling is an essential tool for exploring intrinsic dependence structures among high-dimensional random variables. Much progress has been made for estimating the covariance matrix from a high-dimensional factor model. However, the…

Statistics Theory · Mathematics 2016-10-26 Quefeng Li , Guang Cheng , Jianqing Fan , Yuyan Wang

When dealing with certain kind of complex phenomena the theoretician may face some difficulties -- typically a failure to have access to information for properly characterize the system -- for applying the full power of the standard…

Statistical Mechanics · Physics 2007-05-23 Roberto Luzzi , Áurea R. Vasconcellos , J. Galvão Ramos

Smooth backfitting has proven to have a number of theoretical and practical advantages in structured regression. Smooth backfitting projects the data down onto the structured space of interest providing a direct link between data and…

Statistics Theory · Mathematics 2020-02-07 Munir Hiabu , Enno Mammen , Maria Dolores Martinez-Miranda , Jens Perch Nielsen

Most conspicuous organisms are multicellular and most multicellular organisms develop somatic cells to perform specific, non-reproductive tasks. The ubiquity of this division of labor suggests that it is highly advantageous. In this paper,…

Populations and Evolution · Quantitative Biology 2008-01-18 Martin Willensdorfer

Growth-fragmentation processes describe the evolution of systems of cells which grow continuously and fragment suddenly; they are used in models of cell division and protein polymerisation. Typically, we may expect that in the long run, the…

Probability · Mathematics 2021-01-22 Jean Bertoin , Alexander Watson

The Bargmann-Fock space(or Fock space for short) is a fundamental example of reproducing kernel Hilbert spaces that has found fascinating applications across multiple fields of current interest, including quantum mechanics, time-frequency…

Complex Variables · Mathematics 2025-10-14 Kamal Diki

We describe discrete restricted Boltzmann machines: probabilistic graphical models with bipartite interactions between visible and hidden discrete variables. Examples are binary restricted Boltzmann machines and discrete naive Bayes models.…

Machine Learning · Statistics 2014-04-23 Guido Montufar , Jason Morton

Physical mechanisms of phase separation in living systems can play key physiological roles and have recently been the focus of intensive studies. The strongly heterogeneous and disordered nature of such phenomena in the biological domain…

Statistical Mechanics · Physics 2022-01-28 N. Lauber , O. Tichacek , R. Bose , C. Flamm , L. Leuzzi , T-Y Dora tang , K. Ruiz-Mirazo , D. De Martino

Modeling transformations between arbitrary data distributions is a fundamental scientific challenge, arising in applications like drug discovery and evolutionary simulation. While flow matching offers a natural framework for this task, its…

Machine Learning · Computer Science 2025-10-09 Shiye Su , Yuhui Zhang , Linqi Zhou , Rajesh Ranganath , Serena Yeung-Levy

Considerable insight into the functional activity of proteins and enzymes can be obtained by studying the low-energy conformational distortions that the biopolymer can sustain. We carry out the characterization of these large scale…

Soft Condensed Matter · Physics 2009-11-11 M. Neri , M. Cascella , C. Micheletti

The split covariance intersection filter (split CIF) is a useful tool for general data fusion and has the potential to be applied in a variety of engineering tasks. An indispensable optimization step (referred to as w-optimization) involved…

Systems and Control · Electrical Eng. & Systems 2025-03-11 Hao Li

Similarity functions measure how comparable pairs of elements are, and play a key role in a wide variety of applications, e.g., notions of Individual Fairness abiding by the seminal paradigm of Dwork et al., as well as Clustering problems.…

Machine Learning · Computer Science 2023-10-24 Leonidas Tsepenekas , Ivan Brugere , Freddy Lecue , Daniele Magazzeni

Recent years have seen vast improvements in the ability of rigorous quantum-mechanical methods to treat systems of interest to molecular biology. In this review article, we survey common computational methods used to study such large,…

Biological Physics · Physics 2012-07-05 Brian Kolb , T. Thonhauser

Statistical modeling plays a fundamental role in understanding the underlying mechanism of massive data (statistical inference) and predicting the future (statistical prediction). Although all models are wrong, researchers try their best to…

Methodology · Statistics 2020-06-17 Hangjin Jiang
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