Conferences  >  Mathematics  >  Probability and Statistics, Game Theory

Our workshop covers a broad range of topics, such as complex longitudinal and survival data analysis, high-dimensional data analysis, precision medicine, and artificial intelligence/machine learning methods, among others. Our workshop will have 2 plenary sessions, 24 invited sessions, and a poster session.

American Statistical Association

The Bernoulli–IMS World Congress in Probability and Statistics is held every four years.

University of Waterloo, Canada

The MCQMC conference series is a biennial meeting focused on Monte Carlo (MC) and quasi-Monte Carlo (QMC) methods in scientific computing. The conference attracts between 150 and 200 participants. Its aim is to provide a forum where leading researchers and users can exchange information on the latest theoretical developments and important applications of these methods. Recent conferences have attracted researchers in Markov chain Monte Carlo (MCMC). In a nutshell, MC methods study complex systems by simulations fed by computer-generated pseudorandom numbers. QMC methods replace these random numbers by more evenly distributed (carefully selected) numbers to improve their effectiveness. A large variety of special techniques are developed and used to make these methods more effective in terms of speed and accuracy. The conference focuses primarily on the mathematical study of these techniques, their implementation and adaptation for concrete applications, and their empirical assessment.

Modeling and Simulation,    Scientific Computing and Data Science

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

Algebra,    Geometry and Topology

Casa Matemática Oaxaca (CMO)

The RSS conference brings together the statistics and data science community from across the UK, Europe and around the world to share knowledge and learn about latest developments. With over 600 attendees from around 30 countries and all sectors using statistics and data, this is a must-attend event for professionals, researchers, students and everyone interested in the impactful application of statistics and data science.

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.

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Courses and Events for Math Students and Early Career Researchers,    Geometry and Topology

Living systems operate in space and time, and recent developments in technologies, including spatial omics of tissues and organs, cell-scale structural biology, and planet-scale molecular sampling, are creating exciting new challenges for mathematical modeling, statistical inference and data science.

University of Vienna and the Institute Vienna Circle

Eurandom workshop centre, Department of Mathematics and Computer Science, TU Eindhoven

Topics around Gibbs point processes, such as Bose-Einstein condensation, cristallization, phase-transitions, Gibbs-non-Gibbs, etc.

Eurandom

The goal of the workshop is to bring together researchers that work on various aspects of stochastic interacting systems in continuous space. This includes for example interacting particles in the continuum, their equilibrium and metastable behavior as well as stochastic dynamics of such systems. A special focus of the workshop also lies on the influence of geometry in natural random objects such as Brownian motion, Gibbs point processes and interacting Markovian systems. This EURANDOM event thrives to provide a platform for the lively exchange of national and international researchers on every career level.

Institute for Computational and Experimental Research in Mathematics (ICERM)

The program will explore different perspectives on uncertainty quantification, efficient simulation, and the analysis of complex stochastic systems. The topics covered will include exciting recent developments on efficient methods for approximating quasi-stationary distributions, simulation of equilibrium distributions, information divergences in sensitivity analysis of rare events, large deviations methods for efficient importance sampling, accelerated Monte Carlo via nonlinear PDE, and complex probabilistic models including reflected diffusions and high-dimensional dynamics arising in chemistry and physics.

ICERM;     Email: info@icerm.brown.edu

uncertainty quantification, complex stochastic systems, optimization

Predicative Foundations, Constructive Mathematics and Type Theory, Computation in Higher Types, Extraction of Programs from Proofs

Romanian Society of Industrial and Applied Mathematics and University of Oradea

CAIM series provide a forum for the review of the recent trends in applied and industrial mathematics either from a qualitative or from a numerical point of view.

Email: conferences.caim@yahoo.com

Partial Differential Equations, Dynamical Systems, Mathematical Modeling in Engineering and Life Sciences, Real, Complex, Functional and Numerical Analysis, Probability Theory, Mathematical Statistics, Operations Research, Algebra, Logic, Geometry, Computer Science, Education

Applied Mathematics (in general),    Mathematical Physics

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Modern algorithms for data analysis require the use of advanced probabilistic methods to achieve desirable scalability and accuracy guarantees. At the same time, modern data-analysis tasks require the use of advanced statistics to handle challenges such as testing for multiple hypotheses or identifying dependencies among data points, such as in time series or graphs. Probabilistic methods are also at the core theoretical computer-science areas, such as sublinear algorithms and average-case analysis. To obtain efficient data-analysis algorithms, probabilistic methods require careful balancing of theoretical and practical aspects. This Dagstuhl Seminar brings together researchers interested in statistical and probabilistic methods to design and analyze scalable algorithms for discovering knowledge in large and rich datasets. We plan to cover the following topics, among others.

Information & Knowledge Management, Big Data Computing,    Scientific Computing and Data Science

Eurandom

The purpose is to maintain ISNET's mission of bringing the nuclear physics and statistical sciences communities together to report on the latest progress and to provide a vehicle for educating and enlightening the nuclear physics community in regard to the application of statistical methodologies that enable nuclear physics to reach more quantitatively rigorous scientific conclusions.

Uncertainty quantification and statistical analysis, Emulators and optimizations, Model mixing and data mining, Machine learning, Bayesian inference, Statistics techniques in nuclear experiments, New frontiers of nuclear physics

Multidisciplinary Events in Physics,    Scientific Computing and Data Science

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Non-Bayesian approaches appear to solve many problems that Bayesians once dreamt of solving using Bayesian methods. We thus believe that it is timely and important to rethink and redefine the promises and challenges of Bayesian approaches; and also to elucidate which Bayesian methods might prevail against their non-Bayesian competitors; and finally identify key application areas where Bayes can shine.

Eurandom

The conference will bring together researchers with backgrounds in operations management, statistics, stochastic modelling, data science and control to discuss contemporary queueing-related challenges. The increasing availability of empirical data in the operation of large computer networks and in the management of human service systems is creating new opportunities for study in queueing theory. The objective of the workshop is to highlight and discuss future directions in data-driven queueing that arise in modelling, monitoring and controlling queues, and in dealing with parameter uncertainty, when there is access to operational data.

Joint Research Center for Advanced and Fundamental Mathematics for Industry

Isaac Newton Institute for Mathematical Sciences

The workshop will bring together researchers from different fields to discuss recent advances in Monte Carlo sampling algorithms. Monte Carlo methods have had a profound impact on science and technology for the past 70 years, facilitating major breakthroughs in such diverse areas as statistical physics, computational chemistry and drug discovery, statistical inference and machine learning, econometrics and theoretical computer science, as well as many others.

The workshop is part of a 6 month programme exploring stochastic systems and anomalous diffusion. Anomalous diffusion within the context of sampling refers to the non-Brownian regime. Such anomalous (or non-diffusive) behaviour can be achieved by various means, such as non-reversibility, boundaries and constraints, trapping and intelligent use of gradients. These advances and more will be explored at the workshop.

Wilhelm and Else Heraeus-Foundation

Fluctuations are a fundamental manifestation of the microscopic stochastic/quantum dynamics of physical systems. They are present at very different scales and give rise to a plethora of effects, relevant across various research fields. Understanding the origin of fluctuation-induced phenomena is rapidly becoming important not only for fundamental investigations but also for the characterization of experimental setups and for the opportunities and challenges that they offer to modern technologies. The seminar covers a broad range of subjects having fluctuations as a common denominator. It focuses on current challenges encompassing diverse physical systems both in and out of equilibrium, spanning different scales and configurations.

Metrology and Instrumentation,    Thermodynamics, Fluid Dynamics and Statistical Physics

Institute of Mathematical Statistics (IMS)

The objective of ICSDS is to bring together researchers in statistics and data science from academia, industry, and government in a stimulating setting to exchange ideas on the developments of modern statistics, machine learning, and broadly defined theory, methods, and applications in data science. There will be a student paper award competition, in addition to plenary sessions, and invited, contributed and poster sessions. Young researchers are particularly encouraged to participate, as a portion of the invited sessions will be designated for young researchers.

Information & Knowledge Management, Big Data Computing,    Scientific Computing and Data Science

Simons Laufer Mathematical Sciences Institute (SLMath)

Networks, graph driven algorithms, and dynamics on graphs such as epidemics, random walks and centrality measures all play a major role, both in our daily lives as well as many scientific and engineering disciplines. This introductory workshop will bring together experts and junior researchers in combinatorics, probability, and statistics to share a broad vision of major challenges and objectives, with a primary focus on models of random graphs and their limits, network inference, dynamic processes on networks and algorithms and optimization on random structures.

Network models and random graphs, statistcal learning and network inference, counting and sampling discrete structures, dynamics on networks, probabilistic analysis of network algorithms

Erwin Schrödinger International Institute for Mathematics and Physics (ESI)

Algebra,    Graph Theory and Combinatorics

Institute for Mathematical and Statistical Innovation (IMSI)

This long program will focus on the newest development of UQ methodologies and how they can improve AI systems and provide solutions to modeling complex systems. It will also give an outlook on future UQ directions and challenges. Through all the activities proposed, the program will bring together interested parties, researchers, practitioners, and students, from different areas of UQ, promote communication, and further break down the barriers between disciplines. The program also has a significant mentoring component, which connects researchers and students at different career stages.

Systems theory, Control and Automation,    Implementation and Applications of Artificial Intelligence

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

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

SPA Conferences are organised under the patronage of the Bernoulli Society and may be regarded as the most important series of international meetings on the theory and applications of stochastic processes.

American Statistical Association

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

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

Graph Theory and Combinatorics,    Information Theory, Foundations of Computer Science

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

Institute of Mathematical Statistics

American Statistical Association (ASA)