Conférences  >  Informatique  >  Calcul scientifique et science des données

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

Réseaux de neurones et intelligence artificielle, apprentissage automatique,    Gestion des connaissances, Big Data Computing

The CHEP conference series addresses the computing, networking and software issues for the world’s leading data‐intensive science experiments that currently analyse hundreds of petabytes of data using worldwide computing resources.

CEA, Alternative Energies and Atomic Energy Commission

In addition to promoting the advances in the traditional topics of the conference, encompassing super-computing for nuclear applications and Monte Carlo simulation, SNA + MC2024 will also emphasize novel subjects with strong scientific, technological and societal stakes: the recent breakthroughs in High Performance Computing, environmental issues and energy transition.

Energie nucléaire,    Superordinateur et ordinateur parallèle

Commissariat à l’Energie Atomique et aux énergies alternatives (CEA, France)

In addition to promoting the advances in the traditional areas of interest for this conference, encompassing Monte Carlo simulation and high-performance computing (HPC) methods for nuclear applications, SNA + MC 2024 will also cover novel topics related to emerging scientific and technological challenges, in particular climate and environmental issues, and energy transition.

Energie nucléaire,    Superordinateur et ordinateur parallèle

Society for Industrial and Applied Mathematics (SIAM)

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

Cours et évènements pour étudiants en mathématiques,    Calcul infinitésimal, équations différentielles et intégrales

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

The vision of NFDI4DS is to support all steps of the complex and interdisciplinary research data lifecycle in Data Science and Artificial Intelligence. The overarching objective of NFDI4DS is the development, establishment, and sustainment of a national research data infrastructure for the Data Science and Artificial Intelligence community. The key idea is to work towards increasing the transparency, reproducibility and fairness of Data Science and Artificial Intelligence projects, by making all digital artifacts available, interlinking them, and offering innovative tools and services. Within this Dagstuhl Research Meeting, the NFDI4DS partners will reflect on their progress so far, and will work on their long-term strategy.

Gestion des connaissances, Big Data Computing,    Réseaux de neurones et intelligence artificielle, apprentissage automatique

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

Statistique, Théorie des jeux,    Evénements multidisciplinaires en physique

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

In modern computational systems, the need to handle large-scale inputs imposes interesting computational challenges. Two such challenges are (1) the need to distribute the computation over multiple units, and (2) the dynamic nature of the input, which may undergo changes over time. A particular class of problems studied in these settings is when the input to the computational task is a huge graph. The field of dynamic graph algorithms addresses efficiently processing edge/vertex insertions/deletions in the input graph. In distributed graph algorithms, the input resides across multiple machines, and the goal is to solve the problem while minimizing the number of rounds of communication. Both of these rich research areas have been extensively studied since at least the 1980’s. We know of efficient algorithms for a large variety of tasks, such as shortest paths problems, coloring, subgraph finding, symmetry breaking, approximations, and many more. However, there are still fundamental problems with no known efficient solutions in some of these models, and even more where the exact complexity of computation is yet to be determined. In the recent years, a number of influential works show how transferring ideas from one of these models to the other provides progress on some of the long-lasting open problems. The goal of this Dagstuhl Seminar is to build a bridge between the two research communities of dynamic graph algorithms and distributed computing, by working together on joint research frontiers.

Superordinateur et ordinateur parallèle,    Calcul distribué, cloud computing, informatique en périphérie

Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy

Génie logiciel,    Logiciels

South American Institute for Fundamental Research (ICTP-SAIFR)

Cours et événements pour étudiants en physique,    Réseaux de neurones et intelligence artificielle, apprentissage automatique

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.

Statistique, Théorie des jeux,    Gestion des connaissances, Big Data Computing

Institute for Computational and Experimental Research in Mathematics (ICERM)

In recent years, new opportunities have emerged for pattern detection and identification in applications using data-scientific approaches. These applications include spiral waves in cardiac dynamics, vegetation patterns in arid ecosystems, and cell organization in biological tissues. The aim of this workshop is to bring together researchers at the interface of these diverse aspects of pattern-formation theory, computation, and applications in order to share ideas and identify new challenges and open problems. The scientific program will focus on the use of dynamical systems methods in the study of pattern formation, as well as the integration of dynamics, data, and computation.

ICERM;     Email.: info@icerm.brown.edu

dynamical systems, data science, pattern formation

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

Simons Laufer Mathematical Sciences Institute (SLMath)

In a growing number of applications, one needs to analyze and interpret data coming from massive networks. The statistical problems arising from such applications lead to important mathematical challenges: building novel probabilistic models, understanding the possibilities and limitations for statistical detection and inference, designing efficient algorithms, and understanding the inherent limitations of fast algorithms. The workshop will bring together leading researchers in combinatorial statistics, machine learning, and random graphs in the hope of cross-fertilization of ideas.

combinatorial statistics, random graphs, network inference, network reconstruction, detection, estimation

Réseaux complexes,    Théorie des graphes et combinatoire

NEXT BUSINESS MEDIA

The Data Science Conference (DSC Next 2025) is a premier event set to take place from May 07 - 09, 2025, in Amsterdam. This conference brings together industry experts, data scientists, researchers, and professionals to explore the latest advancements in data science, machine learning, and artificial intelligence. It offers a platform for participants to network, share insights, and discuss the future of data-driven technologies.

EVENT MANAGER;     Tél.: [1 702 551 9568];     Email.: contact@nextbusinessmedia.com

European Molecular Biology Organization (EMBO)

Biologie moléculaire,    Biologie des systèmes

European Molecular Biology Organization (EMBO)