Applications and Techniques for Fast Machine Learning in Science

Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier Duarte, Philip Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci-Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomás E. Müller Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Dongning Guo, Kyle J. Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belina von Krosigk, Shen Wang, Thomas K. Warburton

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DOI: 10.3389/fdata.2022.787421
Published: 2022-04-12
Container: Frontiers in Big Data
Publisher: Frontiers Media SA
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3389/fdata.2022.787421,
  title = {Applications and Techniques for Fast Machine Learning in Science},
  author = {Allison McCarn Deiana and Nhan Tran and Joshua Agar and Michaela Blott and Giuseppe Di Guglielmo and Javier Duarte and Philip Harris and Scott Hauck and Mia Liu and Mark S. Neubauer and Jennifer Ngadiuba and Seda Ogrenci-Memik and Maurizio Pierini and Thea Aarrestad and Steffen Bähr and Jürgen Becker and Anne-Sophie Berthold and Richard J. Bonventre and Tomás E. Müller Bravo and Markus Diefenthaler and Zhen Dong and Nick Fritzsche and Amir Gholami and Ekaterina Govorkova and Dongning Guo and Kyle J. Hazelwood and Christian Herwig and Babar Khan and Sehoon Kim and Thomas Klijnsma and Yaling Liu and Kin Ho Lo and Tri Nguyen and Gianantonio Pezzullo and Seyedramin Rasoulinezhad and Ryan A. Rivera and Kate Scholberg and Justin Selig and Sougata Sen and Dmitri Strukov and William Tang and Savannah Thais and Kai Lukas Unger and Ricardo Vilalta and Belina von Krosigk and Shen Wang and Thomas K. Warburton},
  year = {2022},
  journal = {Frontiers in Big Data},
  doi = {10.3389/fdata.2022.787421},
  url = {https://doi.org/10.3389/fdata.2022.787421}
}

RIS

TY  - JOUR
TI  - Applications and Techniques for Fast Machine Learning in Science
AU  - Allison McCarn Deiana
AU  - Nhan Tran
AU  - Joshua Agar
AU  - Michaela Blott
AU  - Giuseppe Di Guglielmo
AU  - Javier Duarte
AU  - Philip Harris
AU  - Scott Hauck
AU  - Mia Liu
AU  - Mark S. Neubauer
AU  - Jennifer Ngadiuba
AU  - Seda Ogrenci-Memik
AU  - Maurizio Pierini
AU  - Thea Aarrestad
AU  - Steffen Bähr
AU  - Jürgen Becker
AU  - Anne-Sophie Berthold
AU  - Richard J. Bonventre
AU  - Tomás E. Müller Bravo
AU  - Markus Diefenthaler
AU  - Zhen Dong
AU  - Nick Fritzsche
AU  - Amir Gholami
AU  - Ekaterina Govorkova
AU  - Dongning Guo
AU  - Kyle J. Hazelwood
AU  - Christian Herwig
AU  - Babar Khan
AU  - Sehoon Kim
AU  - Thomas Klijnsma
AU  - Yaling Liu
AU  - Kin Ho Lo
AU  - Tri Nguyen
AU  - Gianantonio Pezzullo
AU  - Seyedramin Rasoulinezhad
AU  - Ryan A. Rivera
AU  - Kate Scholberg
AU  - Justin Selig
AU  - Sougata Sen
AU  - Dmitri Strukov
AU  - William Tang
AU  - Savannah Thais
AU  - Kai Lukas Unger
AU  - Ricardo Vilalta
AU  - Belina von Krosigk
AU  - Shen Wang
AU  - Thomas K. Warburton
PY  - 2022
JO  - Frontiers in Big Data
DO  - 10.3389/fdata.2022.787421
UR  - https://doi.org/10.3389/fdata.2022.787421
ER  -

APA

Deiana, A. M., Tran, N., Agar, J., Blott, M., Guglielmo, G. D., Duarte, J., Harris, P., Hauck, S., Liu, M., Neubauer, M. S., Ngadiuba, J., Ogrenci-Memik, S., Pierini, M., Aarrestad, T., Bähr, S., Becker, J., Berthold, A., Bonventre, R. J., Bravo, T. E. M., Diefenthaler, M., Dong, Z., Fritzsche, N., Gholami, A., Govorkova, E., Guo, D., Hazelwood, K. J., Herwig, C., Khan, B., Kim, S., Klijnsma, T., Liu, Y., Lo, K. H., Nguyen, T., Pezzullo, G., Rasoulinezhad, S., Rivera, R. A., Scholberg, K., Selig, J., Sen, S., Strukov, D., Tang, W., Thais, S., Unger, K. L., Vilalta, R., Krosigk, B. V., Wang, S., & Warburton, T. K. (2022). Applications and Techniques for Fast Machine Learning in Science. Frontiers in Big Data. https://doi.org/10.3389/fdata.2022.787421

Source records

crossref · retrieved 2026-09-25T03:15:00.262Z