The Annals of Applied Probability aims to publish research of the highest quality reflecting the varied facets of contemporary Applied Probability. Primary emphasis is placed on importance and originality.
Stochastic Analysis and Applications presents the latest innovations in the field of stochastic theory and its practical applications, as well as the full range of related approaches to analyzing systems under random excitation. In addition, it is the only publication that offers the broad, detailed coverage necessary for the interfield and intrafield fertilization of new concepts and ideas, providing the scientific community with a unique and highly useful service.
Foundations of Data Science invites submissions focusing on advances in mathematical, statistical, and computational methods for data science. Results should significantly advance current understanding of data science, by algorithm development, analysis, and/or computational implementation which demonstrates behavior and applicability of the algorithm. Fields covered by the journal include, but are not limited to Bayesian Statistics, High Performance Computing, Inverse Problems, Data Assimilation, Machine Learning, Optimization, Topological Data Analysis, Spatial Statistics, Nonparametric Statistics, Uncertainty Quantification, and Data Centric Engineering. Expository and review articles are welcome. Papers which focus on applications in science and engineering are also encouraged, however the method(s) used should be applicable outside of one specific application domain.
This journal presents papers that embrace a wide diversity of applied areas, such as physical, chemical, biochemical, environmental topics, and optimum design, as well as stochastic finance. It includes the theories for solving problems, in addition to deterministic and stochastic optimization: partial differential equations dealing with applied problems, such as turbulence, homogenization, and stochastic differential equations occurring in filtering theory and in biology. The journal also features critical surveys of new advances in theory and application.
Stochastic Processes and their Applications publishes papers on the theory and applications of stochastic processes. It is concerned with concepts and techniques, and is oriented towards a broad spectrum of mathematical, scientific and engineering interests.
Characterization, structural properties, inference and control of stochastic processes are covered. The journal is exacting and scholarly in its standards. Every effort is made to promote innovation, vitality, and communication between disciplines.
The journal publishes original research papers of high scientific quality in two areas: Mathematical Modelling, and Numerical Analysis. Mathematical Modelling comprises the development and study - e.g. structure, well-posedness, solution properties - of a mathematical formulation of a problem (or class of problems). Numerical Analysis comprises the formulation and study - e.g. stability, convergence, computational complexity - of a numerical approximation or solution approach to a mathematically formulated problem (or class of problems).
This journal is part of the European Series in Applied and Industrial Mathematics (ESAIM).
Published under the scientific responsibility of the Société de Mathématiques Appliquées et Industrielles (SMAI)
and with the support of the Centre National de la Recherche Scientifique (CNRS)