Conférences - Statistique, Théorie des jeux

We are a community-powered data platforms, engineering, science, and analytics event for software engineers, machine learning experts, deep learning researchers & artificial intelligence buffs who want to discover tools & insights to build new products.

Tél.: [9183894402];     Email.: pete.soderling@datacouncil.ai

data engineering, data science, software engineering

Conception et gestion des bases de données,    Algorithmes

The aim of the workshop is to gather ongoing research on network models, algorithms and applications in the fields of Statistics, Economics, Finance, Political and Social Sciences. Topics are network models in international trade, finance, political systems, social actors, systemic stability, resilience and contagion effects, algorithms for clustering and community detection, centrality measures; new statistics for network analysis; network formation, game theory and network models. Due to the very interdisciplinary nature of the workshop, formal contributions should stress their applicability, while substantial findings should suggest new directions of formal research.

Network models, Communities detection, Dynamic networks, Centrality measures, Game theory

Réseaux complexes,    Finance et sciences économiques

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

The Congreso Latinoamericano de Probabilidad y Estadística Matemática (CLAPEM) is the official meeting of the Sociedad Latino Americana de Probabilidad y Estadística Matemática (SLAPEM), the Latin American Chapter of the Bernoulli Society.

Centre International de Rencontres Mathématiques (CIRM)

American Statistical Association

American Meteorological Society (AMS)

University of Geneva

Simulation,    Cours et évènements pour étudiants en mathématiques

Kyoto University

Statistical Physics Division of the Mexican Society of Physics

The purpose of the meeting is to bring together the national community of physicists working on statistical physics and related areas, in order to exchange knowledge, results and discuss new lines of research. We also invite a group of internationally-well known scientists who have made fundamental contributions in their respective fields. This provides the opportunity to exchange ideas between national and foreign colleagues in a pleasant, inclusive and informal environment.

Physique mathématique,    Thermodynamique, dynamique des fluides et physique statistique

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Réseaux de neurones et intelligence artificielle, apprentissage automatique,    Reconnaissance de formes et traitement d'image, vision par ordinateur

Kyoto University/University of Tsukuba

Astrostatistics is developing fast as astronomy is confronted to huge volumes of data. This constitutes undoubtly a new era through a move from object- to data-driven astrophysics. We can distinguish two types of challenges: the first one is related to the exploration of the data space and the second one is the physical interpretation of the results of this exploration. Astrostatistics cannot be reduced to the technical issues brought by methods and algorithms required to analyse the data. Despite these tools are not part of the cursus of astronomers, things are changing rapidly through schools, training sessions, collaborations with experts (statisticians) as well as developments of specific tools adapted to astronomical data. The use of new techniques pervades the astronomical literature. To convince more and more astronomers to switch to this new approach to do science, it is important to demonstrate the relevance of astrostatistics results.

Tél.: [+39-049-8278233];     Email.: mauro.donofrio@unipd.it

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Uncertainty quantification (UQ) is essential for producing informative computational predictions in a wide range of sciences and engineering. The field relies on a broad range of mathematical and statistical foundations, with associated algorithmic and computational developments. This conference will bring together mathematicians, statisticians, scientists, and engineers with an interest in the development and implementation of uncertainty quantification methods. Major conference themes will include the mathematical and statistical foundations of UQ, applications of UQ in the physical sciences and biosciences, and connections between UQ and machine learning. The goal of the meeting is to provide a forum to share ideas and enhance communication among this diverse group of technical experts, thereby contributing to future advances in the field.

Bernoulli Center (CIB)

Functional data such as space curves, images, and surfaces are seldom sensed directly; curves are often noisily and discretely sampled, images are subject to blurring and deformation, and surfaces are often obtained via indirect linear measurements. Understanding the generation of the observations then requires modelling the act of acquisition, and solving an inverse problem in order to arrive at statistical inferences. This leads to a host of new research questions, from identifiability to trade-offs between statistical optimality and computational feasibility, which also make contact with signal processing and numerical analysis.

Part of the Semester : Functional Data Analysis

Acadia University

Artificial intelligence (AI) is mainly data-driven. It uses statistical methods through human-machine relationships during generation of data, production of algorithm, and prediction of results. The International Workshop on Statistical Methods and Artificial Intelligence will be an annual meeting of researchers in artificial intelligence, statistical methods, machine learning, and related areas.

Artificial Intelligence, Statistical methods, Data Analysis and Data mining, Computational Statistic, Supervised and unsupervised learning, Statistical methodology, Bioinformatics, Medical statistics, Deep Learning, Data Collection and Applications, Data Science and Blockchain Technology, Data Science and Artificial Intelligence, Data Science and Blockchain Technology, Mathematical Statistics, Sampling Techniques and Applications, Statistical Software R, SAS, Python

The advancement in computing and storage capabilities of modern computational clusters fosters use of novel statistical techniques in machine learning and deep networks. Such data-driven techniques allow one to learn model features and characteristics that are difficult for mathematical methods alone to reveal. Many computational methods achieve model and complexity discovery using methods that lie at the nexus of mathematical, statistical, and computational disciplines. Statistical methods often employ "big data" approaches that glean predictive capability from diverse and enormous databases of information. Emerging methods in machine learning and deep networks can provide impressive results. This workshop gathers researchers at the frontier of large-scale statistical computation, data science, tensor decompositions and approximations, and data-driven model learning, to focus on modern challenges that use data to reduce complexity of models.

The Fields Institute

Institute for Mathematical Sciences/National University of Singapore

Random matrix theory is an active branch of probability. It has important applications in statistics, wireless communication and physics, and is closely related to other areas of mathematics, like representation theory, integrable systems, combinatorics, and complex analysis.

Réseaux complexes,    Systèmes complexes et chaos

Bernoulli Center (CIB)

Topological and discrete data such as trees and networks constitute strongly non-Euclidean structures, often beyond the reach of traditional statistical tools. Their analysis is often challenged by computational tractability, as natural constraints such as permutation invariance are computationally hard to implement. Still, such data can be often transposed into more familiar contexts, whether by transformation, asymptotic arguments, or replicated observations. This workshop will explore both modelling and processing of discrete structures, also drawing in areas such as signal processing on graphs and nonparametrics.

Part of the Semester : Functional Data Analysis

Since its inception in 1985, AISTATS has been an interdisciplinary gathering of researchers at the intersection of artificial intelligence, machine learning, statistics, and related areas.

Réseaux de neurones et intelligence artificielle, apprentissage automatique,    Soft computing, algorithmes évolutionnaires, domaine des métaheuristiques, logique floue

EURO Working Group on Stochastic Modelling / Politecnico di Milano

StochMod - the biennial meeting of the EURO Working Group on Stochastic Modelling - is the premier European forum for researchers who have an interest in stochastic modelling. Its eight edition will take place in Milan, at Politecnico di Milano.

American Statistical Association

ICES has been running for more than 20 years. Information about its origins and development was included in the introduction to the December 2014 special issue of the Journal of Official Statistics, which presented papers from ICES-IV.

Methods and Practices for Statistics on Businesses, Farms, and Institutions

We are pleased to announce that the next International Symposium on Nonparametric Statistics will be held in Paphos, Cyprus, from 15-19 June 2020. In the tradition of the successful ISNPS conferences in Chalkidiki (2012), Cadiz (2014), Avignon (2016) and Salerno (2018), this meeting will bring together new and established researchers to consider a broad range of topics from nonparametric and semiparametric statistics. The program will include plenary lectures, invited and contributed talks, and posters.

Centre International de Rencontres Mathématiques (CIRM)

The International Statistical Ecology Conference is a biennial meeting of researchers at the interface between ecology and statistics. At ISEC2020 we are planning an exciting list of keynote speakers that bridge these two disciplines, as well as providing attendees with training opportunities

Mathématiques appliquées (en général),    Écosystèmes, environnement et développement durable

Bernoulli Center (CIB)

Important classes of functional data, such as random measures and random operators, are intrinsically constrained and need to be represented as elements of suitable non-Euclidean spaces, such as Hilbert manifolds. The interplay between the infinite dimensionality of their variation and the non-linearity of their representation space poses novel challenges for statistics, at the interface of several domains, such as shape analysis, stochastic geometry, manifold learning, and functional data analysis. This workshop will bring together experts from these fields to explore these novel challenges and future perspectives.

Part of the Semester : Functional Data Analysis

IWFOS 2020 is jointly organized by Faculty of Science, Masaryk University, Brno, by Faculty of Mathematics and Physics, Charles University, Prague, and by The Union of Czech Mathematicians and Physicists, Brno branch.

The purpose of the series of IWFOS initiated by the working group STAPH of Toulouse at year 2008, is to highlight the major trends in different areas of functional statistics through the exchange of ideas and the promotion of collaboration between researchers from different countries. It aims at contributing to future developments of such areas. The workshop will be a platform for communication, exchange of ideas and interaction for researchers in statistics for infinite-dimensional and high-dimensional problems.

Institute of Mathematics, Faculty of Science, P. J. Šafárik University, Košice

The purpose of the meeting is to bring together researchers sharing an interest in a variety of aspects of statistics and its applications as well as matrix analysis and its applications to statistics, and offer them a possibility to discuss current developments in these subjects. The conference will mainly focus on a number of topics. The topics that have been selected so far include estimation, prediction and testing in linear models, robustness of relevant statistical methods, estimation of variance components appearing in linear models, generalizations to nonlinear models, design and analysis of experiments, including optimality and comparison of linear experiments, and applications of matrix methods in statistics.

Johannes Kepler University (JKU) and the Johann Radon Institute for Computational and Applied Mathematics (RICAM), in Linz, Austria

The Seventh International Conference on Uniform Distribution Theory (UDT 2020) will take place at the Johannes Kepler University (JKU) and the Johann Radon Institute for Computational and Applied Mathematics (RICAM), in Linz, Austria, in July 2020. Linz is the third-largest city of Austria and capital of the state of Upper Austria. Both JKU and RICAM are hosting institutions of the Special Research Program "Quasi-Monte Carlo Methods: Theory and Applications" funded by the Austrian Science Fund, FWF.

This conference brings together four leading statistical communities in the region – the Statistical Society of Australia, the New Zealand Statistical Association, the International Institute of Business Analysis (Special Interest Group for Business Analytics), and the Australian Conference on Teaching Statistics. The aim of this conference is to bring together a broad range of researchers and practioners across a variety of statistical disciplines to facilitate the exchange of theory, methods and applications. With these four societies working together there will be strong program components of interest to a wide diversity of academic, government, and industry colleagues. This includes the full spectrum of delegates from those advancing theoretical methodology to those working on industry applications (in traditional and non-traditional statistical areas). Of particular interest is how Big Data continues to impact all of us.

American Statistical Association

Calcul scientifique,    Simulation

Bernoulli Society, Institute of Mathematical Statistics (IMS)

IMS Annual Meeting

Centre International de Rencontres Mathématiques (CIRM)

Algèbre,    Analyse

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Centre International de Rencontres Mathématiques (CIRM)

RESEARCH SCHOOL

Analyse,    Simulation

Center for Advanced Research for Applied Mathematics and Statistics, Manipal Academy of Higher Education, (MAHE)

Matrix Analysis, Projectors in Linear Models & Multivariate Analysis, Growth Curve Models, Linear Regression Models, Linear Statistical Inference, Modelling Covariance Structures, Multivariate and Mixed Linear Models, Statistics in Big Data Analysis.

Institute for Mathematical Sciences/National University of Singapore

The program aims at studying emerging questions on game theory and applications thereof. Some of the most relevant topics of investigation in game theory revolve around the idea of solution concept for a game, the complexity of its calculation, the ability of agents to learn it, its efficiency, and its nature when the game must satisfy some constraints, such as the ones imposed by an underlying network structure.

Reconnaissance de formes et traitement d'image, vision par ordinateur,    Réseaux complexes

This is the third event of a series of conferences featuring talks by leading researchers in the three areas who are also capable of conveying their message to the audience coming from various regions of these fields. Beside the leading senior figures we also invite as speakers a smaller number of younger colleagues who have already shown their lion's claws.

Email.: pad21-conference@bristol.ac.uk

Probability, Analysis, Dynamical systems

Analyse,    Mathématiques générales et evénement multidisciplinaires

Department of Mathematics & Statistics and the Department of Supply Chain & Business Technology Management of Concordia University in Montreal

In keeping with the long tradition of previous decennial conferences (starting in 1971), this convention is dedicated to all areas of statistical sciences. In addition to the traditional theoretical/applied areas, interdisciplinary research would be encouraged and promoted including major theme areas Applied Statistics, Big Data, Bioinformatics, Biostatistics, Computational Statistics, Data Mining, Data Science, Demography, Econometrics, Health Statistics, Model Selection and Validation, Social Statistics, Supply Chain, Survival Analysis, Stochastic Methods in Ecology, Finance and Engineering.

American Statistical Association

Since 1978, the ANS biennial international conference on Probabilistic Safety Assessment and Analysis has been a forum for communication of major probabilistic risk and safety topics worldwide, including issues, methods, applications, insights, policy, research, and risk-informed regulation experience.

American Statistical Association

American Statistical Association

American Statistical Association

American Statistical Association