Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Stephan Hoyer"'
Autor:
Stephan Rasp, Stephan Hoyer, Alexander Merose, Ian Langmore, Peter Battaglia, Tyler Russell, Alvaro Sanchez‐Gonzalez, Vivian Yang, Rob Carver, Shreya Agrawal, Matthew Chantry, Zied Ben Bouallegue, Peter Dueben, Carla Bromberg, Jared Sisk, Luke Barrington, Aaron Bell, Fei Sha
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 16, Iss 6, Pp n/a-n/a (2024)
Abstract WeatherBench 2 is an update to the global, medium‐range (1–14 days) weather forecasting benchmark proposed by (Rasp et al., 2020, https://doi.org/10.1029/2020ms002203), designed with the aim to accelerate progress in data‐driven weathe
Externí odkaz:
https://doaj.org/article/26fd487748a44dd98181f82522f88510
Autor:
Ali Bashir, Qin Yang, Jinpeng Wang, Stephan Hoyer, Wenchuan Chou, Cory McLean, Geoff Davis, Qiang Gong, Zan Armstrong, Junghoon Jang, Hui Kang, Annalisa Pawlosky, Alexander Scott, George E. Dahl, Marc Berndl, Michelle Dimon, B. Scott Ferguson
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-11 (2021)
Current aptamer discovery approaches are unable to probe the complete space of possible sequences. Here, the authors use machine learning to facilitate the development of DNA aptamers with improved binding affinities, and truncate them without signif
Externí odkaz:
https://doaj.org/article/9508da0079cf405d9f6f644c1119f62f
Publikováno v:
PeerJ, Vol 8, p e8594 (2020)
Profiling cellular phenotypes from microscopic imaging can provide meaningful biological information resulting from various factors affecting the cells. One motivating application is drug development: morphological cell features can be captured from
Externí odkaz:
https://doaj.org/article/d6632caac08b430a8bc534fa3dbdf415
Autor:
Samuel J. Yang, Marc Berndl, D. Michael Ando, Mariya Barch, Arunachalam Narayanaswamy, Eric Christiansen, Stephan Hoyer, Chris Roat, Jane Hung, Curtis T. Rueden, Asim Shankar, Steven Finkbeiner, Philip Nelson
Publikováno v:
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-9 (2018)
Abstract Background Large image datasets acquired on automated microscopes typically have some fraction of low quality, out-of-focus images, despite the use of hardware autofocus systems. Identification of these images using automated image analysis
Externí odkaz:
https://doaj.org/article/5d2ce73d279747d2bfbef81a96bfc6be
Autor:
Stephan Hoyer, Joe Hamman
Publikováno v:
Journal of Open Research Software, Vol 5, Iss 1 (2017)
xarray is an open source project and Python package that provides a toolkit and data structures for N-dimensional labeled arrays. Our approach combines an application programing interface (API) inspired by pandas with the Common Data Model for self-d
Externí odkaz:
https://doaj.org/article/35badf73a9ba4dbcaf44ec7df3054f47
Autor:
Stephan Hoyer, Filippo Caruso, Simone Montangero, Mohan Sarovar, Tommaso Calarco, Martin B Plenio, K Birgitta Whaley
Publikováno v:
New Journal of Physics, Vol 16, Iss 4, p 045007 (2014)
We explore the feasibility of the coherent control of excitonic dynamics in light-harvesting complexes, analyzing the limits imposed by the open nature of these quantum systems. We establish feasible targets for phase and phase/amplitude control of t
Externí odkaz:
https://doaj.org/article/d1cb5f9670f34420807ff476dc5d7fef
Autor:
Joseph Hamman, Anderson Banihirwe, Aureliana Barghini, Alessandro Amici, Stephan Hoyer, Deepak Cherian
A proposal to develop new labelled array data structures for the scientific Python ecosystem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9dc8fea4ef27959108f2ef668fb8069e
Publikováno v:
2021 IEEE International Joint EMC/SI/PI and EMC Europe Symposium.
The computational challenges encountered in the large-scale simulations are accompanied by those from data-intensive computing. In this work, we proposed a distributed data pipeline for large-scale simulations by using libraries and frameworks availa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b787cc2228a85373b4eeb0a85f8947e7
https://doi.org/10.1109/emc/si/pi/emceurope52599.2021.9559316
https://doi.org/10.1109/emc/si/pi/emceurope52599.2021.9559316
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America
The numerical solution of partial differential equations (PDEs) is challenging because of the need to resolve spatiotemporal features over wide length and timescales. Often, it is computationally intractable to resolve the finest features in the solu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91b9d5638cc1edb360cc83525a7eb192
http://europepmc.org/articles/PMC6681734
http://europepmc.org/articles/PMC6681734
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America
Significance Accurate simulation of fluids is important for many science and engineering problems but is very computationally demanding. In contrast, machine-learning models can approximate physics very quickly but at the cost of accuracy. Here we sh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::064b110c13a440805d52041919a385da
https://doi.org/10.1073/pnas.2101784118
https://doi.org/10.1073/pnas.2101784118