# Mathematics

In this discipline: 206,470 papers · 1,215 groups

## Discipline summary

Mathematics is the study of the structure, order and relationships of and between numbers, quantities, forms and space. Considered to be the underlying language of science, it seeks to establish truth through abstraction and formal logic. Pure mathematics, or speculative mathematics, solves abstract problems as an end in itself. Applied mathematics solves practical problems in science, engineering and business by studying and applying mathematical principles and sometimes results in the formulation of new disciplines, such as statistics or game theory.

## Popular papers

1. Introduction This is a concise summary of recommended features in LATEX and a couple of extension packages for writing math formulas. Readers needing greater depth of detail are referred to the sources listed in the bibliography, especially…
2. Matrix identities, relations and approximations. A desktop reference for quick overview of mathematics of matrices.
3. Despite application of cryogen spray (CS) precooling, customary treatment of port wine stain (PWS) birthmarks with a single laser pulse does not result in complete lesion blanching for a majority of patients. One obvious reason is nonselective…
4. Over the second half of the 20th century the subject area loosely referred to as numerical analysis of partial differential equations (PDEs) has undergone unprecedented development. At its practical end, the vigorous growth and steady…
5. In most major universities one of the three or four basic first-year graduate mathematics courses is algebraic topology. This introductory text is suitable for use in a course on the subject or for self-study, featuring broad coverage and a readable…
6. Choosing good problems is essential for being a good scientist. But what is a good problem, and how do you choose one? The subject is not usually discussed explicitly within our profession. Scientists are expected to be smart enough to figure it out…
7. We propose a new method for estimation in linear models. The "lasso" minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of the nature of this constraint it tends to…
8. The Conjugate Gradient Method is the most prominent iterative method for solving sparse systems of linear equations. Unfortunately, many textbook treatments of the topic are written with neither illustrations nor intuition, and their victims can be…
9. We are developing a dual panel breast-dedicated PET system using LSO scintillators coupled to position sensitive avalanche photodiodes (PSAPD). The charge output is amplified and read using NOVA RENA-3 ASICs. This paper shows that the coincidence…
10. Investigators have modeled oceanic and atmospheric vortices in the laboratory in a number of different ways, employing background rotation, density effects, and geometrical confinement. In this article, we address barotropic vortices in a rotating…
11. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org/.
12. An s stage k name snowball sampling procedure is defined as follows: A random sample of individuals is drawn from a given finite population. (The kind of random sample will be discussed later in this section.) Each individual in the sample is asked…
13. The Akzo Nobel research laboratories formulated this problem in their study of the penetration of radio-labeled antibodies into a tissue that has been infected by a tumor. This study was carried out for diagnostic as well as therapeutic purposes.…
14. Preface to the Second Edition; Preface to the First Edition; Chapter 1: Background in Linear Algebra; Chapter 2: Discretization of Partial Differential Equations; Chapter 3: Sparse Matrices; Chapter 4: Basic Iterative Methods; Chapter 5: Projection…
15. Spatstat is a package for analyzing spatial point pattern data. Its functionality includes exploratory data analysis, model-fitting, and simulation. It is designed to handle realistic datasets, including inhomogeneous point patterns, spatial…
16. Computational fluid dynamics (CFD) modeling of trickle-bed reactors with detailed interstitial flow solvers has remained elusive mostly due to the extreme CPU and memory intensive constraints. Here, we developed a comprehensible and scalable CFD…
17. The Akzo Nobel research laboratories formulated this problem in their study of the penetration of radio-labeled antibodies into a tissue that has been infected by a tumor. This study was carried out for diagnostic as well as therapeutic purposes.…
18. The recent development of various methods of modulation such as PCM and PPM which exchange bandwidth for signal-to-noise ratio has intensified the interest in a general theory of communication. A basis for such a theory is contained in the important…
19. During the past decade there has been an explosion in computation and information technology. With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data…
20. A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many…

## Popular groups

1. Collection of papers describing basic algorithms and topics in machine learning, with applications in computer vision and natural language processing.
2. A group for the discussion on everything related to Statistics.
3. New way to share a little bit about biostatistics. Absolutly not an expert group, just tools to help physician reading and writings paper. I'll be…
4. articles mainly about Bayesian statistics, Monte Carlo methods, graphical models, Bayesian phylogenetics.
5. Population genetics is the study of allele frequency distribution and change under the influence various evolutionary processes such as natural…