Konferenzen zum Thema Wissenschaftliches Rechnen in den Vereinigten Staaten (USA)

Society for Industrial and Applied Mathematics (SIAM)

Sponsored by the SIAM Activity Group on Computational Science and Engineering.

ICERM - The Institute for Computational and Experimental Research in Mathematics

Deep learning is profoundly reshaping the research directions of entire scientific communities across mathematics, computer science, and statistics, as well as the physical, biological and medical sciences . Yet, despite their indisputable success, deep neural networks are known to be universally unstable. That is, small changes in the input that are almost undetectable produce significant changes in the output. This happens in applications such as image recognition and classification, speech and audio recognition, automatic diagnosis in medicine, image reconstruction and medical imaging as well as inverse problems in general. This phenomenon is now very well documented and yields non-human-like behaviour of neural networks in the cases where they replace humans, and unexpected and unreliable behaviour where they replace standard algorithms in the sciences.

Tel.: [4018635030];     Email: programstaff@icerm.brown.edu

Email: https://www.jlab.org/conference/CHEP2021

Angewandte Mathematik (allgem.),    Massenspektrometrie, Chromatographie und Kernspinresonanzspektroskopie

Angewandte Mathematik (allgem.),    Massenspektrometrie, Chromatographie und Kernspinresonanzspektroskopie

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, Astrophysik und Kosmologie,    Teilchenphysik und Felder

Computerphysik und Numerische Simulation,    Angewandte Mathematik (allgem.)