Conférences - Calcul scientifique

Data science and optimization are closely related. On the one hand, many problems in data science can be solved using optimizers, on the other hand optimization problems stated through classical models such as those from mathematical programming cannot be considered independent of historical data. Examples are ample: Machine Learning (ML) often relies on optimization techniques such as linear or integer programming; reasoning systems have been applied to constrained pattern and sequence mining tasks; a parallel development of metaheuristic approaches has taken place in the domains of data mining and machine learning; methods aimed at high level combinatorial optimization have been shown to strongly profit from configuration, algorithm selection and tuning tools building on historical data; ML models can be embedded in combinatorial optimization problems to address hard-to-model systems, or for validation of the ML model itself; “predict, then optimize” scenarios can be dealt with in an integrated fashion to improve considerably the solution quality.

Simulation,    Réseaux de neurones et intelligence artificielle, apprentissage automatique

Casa Matemática Oaxaca (CMO) in Mexico, and the Banff International Research Station for Mathematical Innovation and Discovery (BIRS) in Banff, Canada

The development of high-performance simulation tools for real-life problems involving fluid flows and related transport phenomena frequently requires the use of numerical methods that are high-order accurate in space and time and preserve important physical properties of certain quantities of interest (such as nonnegativity of the water height in shallow water equation models). In recent years, the state of the art in the development of such schemes was significantly advanced by a breakthrough in theoretical analysis which has provided illuminating insights into the properties of existing methods and new design criteria for the development of improved solution strategies. However, many theoretical aspects of physics-aware discretization techniques still require further exploration or have not been put into practice so far. The purpose of this workshop is to bridge the gap between the mathematical theory and engineering practice.

Cours et évènements pour étudiants en mathématiques,    Simulation

Institute for Pure and Applied Mathematics (IPAM), UCLA

The aim of this program is to connect efforts of the mathematical and physical sciences communities to address the latest advances and new challenges on the understanding of multi-messenger astronomy. The IPAM program will comprise four workshops, each addressing a different topic: the generation of catalogs of waveform templates; the discussion of the mathematical modeling of the equations governing strong relativistic systems; parameter estimation of astrophysical sources of gravitational waves; and the state of the art of big data and deep learning techniques for GW data analysis.

Astronomie, astrophysique et cosmologie,    Physique des hautes énergies, des particules et des champs

Institute for Pure and Applied Mathematics (IPAM), Los Angeles, CA

Part of the Long Program Mathematical and Computational Challenges in the Era of Gravitational Wave Astronomy

The Society of Exploration Geophysicists of Japan (SEGJ)

Road ahead for geophysics in digital society: Acquisition, processing, and interpretation

Géophysique et géologie,    Evénement multidisciplinaires ou générales en informatique

Institute for Pure and Applied Mathematics (IPAM).

Part of the Long Program Mathematical and Computational Challenges in the Era of Gravitational Wave Astronomy

CIRM – Centre International de Rencontres Mathématiques

HSE Tikhonov Moscow Institute of Electronics and Mathematics

FIT-M - Is an effective working format of three sites, the joint result of which will allow you to quickly understand the main trends in the use of modern information technologies in the practice of scientific fundamental and applied research, industrial production management and business processes

Email.: info@fit-m.org

- Mathematical modeling and artificial intelligence in the natural sciences ✓ Algorithms and Applications of Machine Learning - Intelligent Decision Making and Applied Game Theory - Computational social science and network analysis - Digital humanities, computational philosophy, and computer science ✓ Multi-Agent Systems - Technological Mining - Testing of Complex Systems - Machine learning and plasma physics (Special Section)Mathematical modeling and artificial intelligence in the natural sciences ✓ Algorithms and Applications of Machine Learning - Intelligent Decision Making and Applied Game Theory - Computational social science and network analysis - Digital humanities, computational philosophy, and computer science ✓ Multi-Agent Systems - Technological Mining - Testing of Complex Systems - Machine learning and plasma physics (Special Section)

Evénement multidisciplinaires ou générales en informatique,    L'Internet des objets (IoT) et réseau de capteurs

The central aim of this conference is to explore multi-disciplinary research. It focuses on Quantum Computing and Quantum Simulations, Exa-scale Computing and its Applications, Metaheuristics in Science and Technology, Numerical Linear Algebraic Methods for Large Scale Scientific Computing, and Quantum Communications and Quantum Cryptography for Scientists, Researchers and Engineers. Its impact is already being felt in many areas of Sciences and Engineering disciplines. Current research in computational science requires multi-disciplinary knowledge, not only in sciences and engineering but also in technologies of computing. This conference offers academic researchers, developers and practitioners an opportunity to discuss various aspects of computational science and engineering related computational methods and problems solving techniques for science and engineering research.

CZES-nd

The previous editions of ICCDA were held in Florida Polytechnic University, Lakeland, Northern Illinois University (NIU) DeKalb, University of Hawaii Maui College, Kahului, Silicon Valley, USA. ICCDA 2022 conference will be located in Sanya, China during Feb. 18-20, 2021.

Tél.: [+86 138 8010 4517];     Email.: Nazal@sina.com

Mathematical, probabilistic and statistical models and theories; Machine learning theories, models and systems; Knowledge discovery theories, models and systems; Manifold and metric learning; Deep learning; Scalable analysis and learning; Non-iidness learning; Heterogeneous data/information integration; Data pre-processing, sampling and reduction; Dimensionality reduction; Feature selection, transformation and construction; Large scale optimization; High performance computing for data analytics; Architecture, management and process for data science;

The SIAM Conference on Parallel Processing for Scientific Computing is sponsored by the SIAM Activity Group on Supercomputing.

The SAMO conference is devoted to advances in research on sensitivity analysis methods and their interdisciplinary applications. The SAMO conferences are held every three years. The aim of the SAMO conferences is to bring together users of sensitivity analysis in all disciplines of science. Sensitivity analysis methods are powerful tools in physics, operations research, chemistry, biology, engineering, environmental science, nuclear and industrial safety, economics and finance.

Statistique, Théorie des jeux,    Simulation

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

Cours et évènements pour étudiants en mathématiques,    Algèbre

Physique numérique,    Mathématiques appliquées (en général)

ISMP is the triennial international congress of mathematical optimization and organized by the Mathematical Optimization Society (MOS). The 24th ISMP will be convened in Beijing and locally organized by the Operations Research Society of China (ORSC).

The goal of this long program proposal is to bring together senior and junior applied mathematicians, physicists, chemists, materials scientists, engineers and biologists to discuss and debate on the current status and future perspectives of modern microscopy using computation, mathematics and modeling. Cryo-EM has revolutionized biology and life science (including very recently solving the 3D atomic structure of COVID-19, which has been greatly facilitating the development of the vaccines) and aberration-corrected electron optics and high brightness X-ray sources have transformed physical science imaging. The next steps in these fields will advance by orders of magnitude the temporal resolution and energy resolution, while maintaining atomic spatial resolution, in a variety of sample environments from near zero Kelvin in vacuum to temperatures of a thousand degrees in a highly corrosive atmosphere. These advances will transform research in macromolecules, materials, energy technologie

Mathématiques appliquées (en général),    Microscopie

Developing multi-dimensional electron microscopy would have transformative impact in physics, chemistry, materials science, nanoscience and other fields. Advancing the field requires integration of state-of-the-art atomic electron tomography, ptychography, 4D scanning transmission electron microscopy and spectroscopic techniques as well as powerful computational algorithms and mathematical modeling. This workshop will provide the opportunity to present and exchange ideas, share data, and introduce new tools and develop new imaging paradigms needed in a variety of fields.

Mathématiques appliquées (en général),    Microscopie

The implementation of advanced algorithms with user-friendly software packages has made the cryo-EM method straightforward in practice. Despite these exciting advances, major challenges still remain, such as higher throughput, mapping continuous deformations, reconstruction of small macromolecules, and in sample preparation. For pleomorphic structures, cryo-electron tomography (cryo-ET) is the method of choice, but it is typically limited to lower resolution compared to cryo-EM, and it remains a daunting challenge to determine macromolecular structures in situ at high resolution. Overcoming these major challenges in cryo-EM and cryo-ET requires significant advances in sample preparation, hardware development and computational algorithms. The goal of this workshop is to bring together leading experts in cryo-EM, biologists, applied mathematicians and physicists to discuss and debate the current challenges and future perspectives of this very exciting cross-disciplinary field.

Mathématiques appliquées (en général),    Microscopie

The aim of this program is to foster the development of new mathematical tools and formalisms that will enable a new generation of ultra-scalable algorithms for a broad range of applications in computational materials science. Topics of interest will include strategies for scalable single-scale simulations, novel massively-parallel scale-bridging algorithms, and integration of extreme-scale computing into experimental and data science workflows. The program will bring together applied mathematicians, materials scientists, computer scientists, and method developers interested in unlocking the potential of upcoming exascale architectures through novel mathematical approaches.

The organizers of the XVI International Conference on Stochastic Programming (ICSP2022) are honored to host the tri-annual Conference at the University of California, Davis Graduate School of Management. The ICSP is the premier event of the Stochastic Programming Society (SPS) , a technical session of the Mathematical Optimization Society that brings together researchers who work on decisions under uncertainty, practitioners in the industrial and institutional sectors share recent theoretical and applied results. The conference aims to present the state-of-the-art in this field as well as neighboring scientific areas.