Conferences  >  Mathematics  >  Probability and Statistics, Game Theory

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)

TU Wien, Austria

The third Vienna Congress on Mathematical Finance will be held once again at the campus of WU Vienna. The conference will bring together leading experts from various fields of Mathematical Finance. The program will feature plenary lectures, parallel sessions with invited and contributed talks as well as poster sessions. Moreover, there will be an attractive social program. The VCMF 2025 follows the successful previous editions VCMF 2019 and VCMF 2016.

VCMF Conference Managers;     Email: vcmf2025@fam.tuwien.ac.at

Financial Economics, Green und Sustainable Finance, Insurance, Statistics for Financial Markets and Large Language Models, Mean Field Games and Stochastic Control, New Technologies in Finance and Insurance, Optimal Transport, Portfolio Optimisation, Risk Management, Rough Analysis in Finance and Insurance

Mathematical Economics and Finance,    Applied Mathematics (in general)

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)