Conferences  >  Mathematics  >  Probability and Statistics, Game Theory

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

The International Centre for Mathematical Sciences (ICMS)

Mathematical representations of complex institutions will enable us to move beyond the limits of tools such as game theory by introducing the composability, abstraction, and modularity of software engineering. With formal representations, scholars can begin to imagine a computationally aided design (CAD) of arbitrarily complex institutions. For example, within recent frameworks like "categorical game theory," a focus of this workshop, researchers from across the social sciences can compose systems of economic games into complex governance institutions. With such advances, computationally inclined economists, sociologists, political scientists, and natural resource scholars gain a common language for representing fundamental challenges in the design of social systems.

Optimization Theory, Operational Research,    Applied Mathematics (in general)

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

CIRM – Centre International de Rencontres Mathématiques

We plan to dedicate the 2023 – 2025 series of conferences to challenges and emerging topics in the area of mathematical statistics driven by the adventure of artificial intelligence. Tremendous progress has been made in building up powerful machine learning algorithms such as random forests, gradient boosting or neural networks. These models are exceptionally complex and difficult to interpret but offer enormous opportunities in many areas of application going from science, public policies to business. These sophisticated algorithms are often called “black boxes” as they are very hard to analyze. The widespread use of such predictive algorithms raises extremely important questions of replicability, reliability, robustness or privacy protection. The proposed series of conferences is dedicated to new statistical methods built around these black-box algorithms that leverage their power but at the same time guarantee their replicability and reliability. The second conference of the program will highlight recent theoretical advances in inference for high-dimensional statistical models based on the interplay of techniques from mathematical statistics, machine learning and theoretical computer science.

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)

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

In this Dagstuhl Seminar, we are gathering several researchers from different communities (approximation algorithms, algorithmic game theory, operations research, online algorithms, learning theory) that have been interested in this or related questions from different angles. The goal is developing new techniques, identifying new models and directions, and solving some of the many open problems related to the above question.

Modeling and Simulation,    Applied Mathematics (in general)

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

Banach Center

Analysis,    Geometry and Topology

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

Institute of Mathematical Statistics

American Statistical Association (ASA)