Applications and Techniques for Fast Machine Learning in Science

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In this community review report, we discuss applications and techniques for fast machine learning (ML) in science—the concept of integrating powerful ML methods into the real-time experimental data processing loop to accelerate scientific discovery. The material for the report builds on two workshop...

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Detalles Bibliográficos
Autores principales: Deiana, Allison McCarn, Tran, Nhan, Agar, Joshua, Blott, Michaela, Di Guglielmo, Giuseppe, Duarte, Javier, Harris, Philip, Hauck, Scott, Liu, Mia, Neubauer, Mark S., Ngadiuba, Jennifer, Ogrenci-Memik, Seda, Pierini, Maurizio, Aarrestad, Thea, Bähr, Steffen, Becker, Jürgen, Berthold, Anne-Sophie, Bonventre, Richard J., Müller Bravo, Tomás E., Diefenthaler, Markus, Dong, Zhen, Fritzsche, Nick, Gholami, Amir, Govorkova, Ekaterina, Guo, Dongning, Hazelwood, Kyle J., Herwig, Christian, Khan, Babar, Kim, Sehoon, Klijnsma, Thomas, Liu, Yaling, Lo, Kin Ho, Nguyen, Tri, Pezzullo, Gianantonio, Rasoulinezhad, Seyedramin, Rivera, Ryan A., Scholberg, Kate, Selig, Justin, Sen, Sougata, Strukov, Dmitri, Tang, William, Thais, Savannah, Unger, Kai Lukas, Vilalta, Ricardo, von Krosigk, Belina, Wang, Shen, Warburton, Thomas K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Big Data
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9041419/
https://www.ncbi.nlm.nih.gov/pubmed/35496379
http://dx.doi.org/10.3389/fdata.2022.787421

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9041419/
https://www.ncbi.nlm.nih.gov/pubmed/35496379
http://dx.doi.org/10.3389/fdata.2022.787421

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