Konferenzen zum Thema Angewandte Mathematik (allgem.) in den Vereinigten Staaten (USA)

The following meetings will be held jointly: SIAM 2022 SIAM Annual Meeting (AN22) SIAM Conference on Applied Mathematics Education (ED22) SIAM Conference on the Life Sciences (LS22) SIAM Conference on Mathematics of Planet Earth (MPE22)

The SIAM Annual Meeting provides a broad view of the state of the art in applied mathematics, computational science, and their applications through invited presentations, prize lectures, minitutorials, minisymposia, contributed presentations and posters.

The following meetings will be held jointly: SIAM 2022 SIAM Annual Meeting (AN22) SIAM Conference on Applied Mathematics Education (ED22) SIAM Conference on the Life Sciences (LS22) SIAM Conference on Mathematics of Planet Earth (MPE22)

Didaktik in der Wissenschaft,    Ausbildung

The following meetings will be held jointly: SIAM 2022 SIAM Annual Meeting (AN22) SIAM Conference on Applied Mathematics Education (ED22) SIAM Conference on the Life Sciences (LS22) SIAM Conference on Mathematics of Planet Earth (MPE22)

Geophysik und Geologie,    Meteorologie und Klimaveränderung

Georgia Institute of Technology

Topology Students Workshop is a biennial conference at Georgia Insitute of Technology that started in 2012. The first three were funded by a National Science Foundation Career Award and the fourth is funded by an independent grant from the National Science Foundation. The workshop serves as both a research conference and a professional development workshop for graduate students in the fields of geometric group theory, geometry, and topology. Each workshop has included approximately 50 participants and 10 mentors at various career stages. The Topology Students Workshop is unique in its emphasis on community building, professional development, and communication skills.

Computerphysik und Numerische Simulation,    Wissenschaftliches Rechnen und Datenwissenschaft

This workshop will explore a unique combination of data- and model-driven approach by inviting mathematicians and scientists focusing on neurosciences and beyond. We will have an in-depth discussion of data-driven modeling techniques, dynamics reconstruction and characterization over multiple scales treating the underlying systems as structures in space as well as structures in time. Problems to be discussed include: predicting critical transitions from multivariate time series; extracting interactions between brain areas and the effects of anaesthetics; understanding the effects pathologies in the network connectivity and modeling ways to alleviate them; introducing and studying models that depart from functional connectivity. This workshop will include a poster session; a request for posters will be sent to registered participants in advance of the workshop.

Komplexe Netzwerke,    Neurologie

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

Mikroskopie,    Wissenschaftliches Rechnen und Datenwissenschaft

Wissenschaftliches Rechnen und Datenwissenschaft,    Informationstheorie und Grundlagen der Informatik

ICACGA is an international conference focused on advanced computational applications of Geometric Algebra (GA) and related hypercomplex algebras such as quaternions and octonions. The reasons for investigating hypercomplex algebras for enabling advanced computational applications and, more specifically, data-centric applications range from theoretical aspects such as the unification of many mathematical systems into one easy-to-understand mathematical framework with an intuitive exploration of geometric objects and geometric operations to computational advantages such as direct integration of GA with standard programming languages, compactness and robustness of algorithms, implicit use of parallelism, and high runtime performance.

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.

Mikroskopie,    Wissenschaftliches Rechnen und Datenwissenschaft

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.

Mikroskopie,    Wissenschaftliches Rechnen und Datenwissenschaft

Institute for Pure and Applied Mathematics (IPAM)

For molecular systems we know the laws of physics to extreme precision. Yet, our ability to compute properties of these systems to numerical precision is very limited. This is mainly due to two sources of computational intractability: quantum mechanics and chaos. On one side, the accurate solution of the Schrödinger equation for large molecular systems is computationally prohibited. One the other side, even if we knew the forces exactly, the dynamical equations for the atoms would exhibit chaotic behaviour, which implies that, just as the weather, we have limited capacity to predict future trajectories. Some aspects of these systems remain predictable at a macroscopic scale, but they require completely different variables, such as pressure, temperature and entropy. We call this emergent theory thermodynamics.

In the completely different discipline of machine learning, a fairly similar phenomenon takes place. The microscopic variables of an image are given by its constituent pixel values. When we analyse the image with a deep neural network (DNN), we will detect edges in the first layer, corners in the next layer, then the object parts and finally, at the top of the neural network, entire objects. We understand the world at the “emergent” level of objects and their relations, not at the level of pixels and edges. In deep learning (DL) emergence happens automatically through learning and some inductive biases such as symmetries.

A major question we want to address in this workshop is whether we can apply the same learning paradigm to the field of molecular science to learn the correct emergent variables and dynamics.

Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen,    Simulation

Society for Industrial and Applied Mathematics (SIAM)

Numerische Analysis,    Algorithmen und Datenstrukturen

Society for Industrial and Applied Mathematics (SIAM)

Society for Industrial and Applied Mathematics (SIAM)

Society for Industrial and Applied Mathematics (SIAM)

The SIAM Annual Meeting provides a broad view of the state of the art in applied mathematics, computational science, and their applications through invited presentations, prize lectures, minitutorials, minisymposia, contributed presentations and posters.

Society for Industrial and Applied Mathematics (SIAM)