Zobrazeno 1 - 10
of 105
pro vyhledávání: '"Chris A. Mattmann"'
Publikováno v:
Data Science Journal, Vol 4, Pp 171-188 (2006)
Successful resource discovery across heterogeneous repositories is highly dependent on the semantic and syntactic homogeneity of the associated resource descriptions in each repository. Ideally, consistent resource descriptions are easily extracted f
Externí odkaz:
https://doaj.org/article/415c853e830f4d2c882b94f7ccb2589b
Autor:
Tim Allison, Ryan Stonebraker, Anastasija Mensikova, Chris A. Mattmann, Philip Southam, Wayne Burke
Publikováno v:
SP Workshops
Parsing untrusted data is notoriously challenging. Failure to handle maliciously crafted data correctly can (and does) lead to a wide range of vulnerabilities. The Language-theoretic security (LangSec) philosophy seeks to obviate the need for develop
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::12950e34a7195de14efcdec50f604deb
https://doi.org/10.1109/spw53761.2021.00025
https://doi.org/10.1109/spw53761.2021.00025
Autor:
Yarin Gal, Chris A. Mattmann, Alexander Lavin, Danny Lange, Siddha Ganju, Ciarán M. Gilligan-Lee, Sujoy Ganguly, Dava J. Newman, Adam Gibson, Alessya Visnjic, James Parr, Amit Sharma, Eric P. Xing, Atılım Güneş Baydin
The development and deployment of machine learning (ML) systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. The lack of diligence can lead to technical debt, scope creep and misaligned objectives
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be9115224d84198d48754bcd1fbbe4c7
https://doi.org/10.21203/rs.3.rs-133138/v1
https://doi.org/10.21203/rs.3.rs-133138/v1
While there are more than 7000 languages in the world, most translation research efforts have targeted a few high-resource languages. Commercial translation systems support only one hundred languages or fewer, and do not make these models available f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b69cddd698528240fec2bcf98705c4e3
Publikováno v:
2020 IEEE/ACM Fourth Workshop on Deep Learning on Supercomputers (DLS)
DLS@SC
DLS@SC
We all have questions. About today's temperature, scores of our favorite baseball team, the Universe, and about vaccine for COVID-19. Life, physical, and natural scientists have been trying to find answers to various topics using scientific methods a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd178474516c3de40900f90f06eceffb
Autor:
Hiya Roy, Hyoshin Park, Shoya Higa, Virisha Timmaraju, Jacek Sawoniewicz, Chris A. Mattmann, Kyohei Otsu, Shunichiro Nomura, Yumi Iwashita, Larkin Folsom, Gabrielle Hedrick, Sami Sahnoune, Sourish Ghosh, Olivier Lamarre, Kathryn M. Stack, Hemanth Sarabu, Shreyansh Daftry, Masahiro Ono, Sean Suehr, Brandon Rothrock, Dicong Qiu, Christopher Laporte, Annie Didier, Tanvir Islam, Vivian Z. Sun
Publikováno v:
2020 IEEE Aerospace Conference.
MAARS (Machine leaning-based Analytics for Automated Rover Systems) is an ongoing JPL effort to bring the latest self-driving technologies to Mars, Moon, and beyond. The ongoing AI revolution here on Earth is finally propagating to the red planet as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb000f2550e24c2adfdf8091d0846dd0
https://doi.org/10.1109/aero47225.2020.9172271
https://doi.org/10.1109/aero47225.2020.9172271
Publikováno v:
Space Weather. 16:1817-1846
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a7d53d106586d073ce27537c7c78e27c
https://doi.org/10.1029/2018sw002018
https://doi.org/10.1029/2018sw002018
Publikováno v:
PLoS ONE
PLoS ONE, Vol 15, Iss 3, p e0230114 (2020)
PLoS ONE, Vol 15, Iss 3, p e0230114 (2020)
Nowcasting of precipitation is a difficult spatiotemporal task because of the non-uniform characterization of meteorological structures over time. Recently, convolutional LSTM has been shown to be successful in solving various complex spatiotemporal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad0649fb4acfdb04ba69faa57eb4f23c
https://pubmed.ncbi.nlm.nih.gov/32160237
https://pubmed.ncbi.nlm.nih.gov/32160237
Autor:
Chris A. Mattmann, Zhao Zhang
Publikováno v:
DLS@SC
Facial recognition is a tractable problem today because of the prevalence of Deep Learning implementations. Approaches for creating structured datasets from unstructured web data are more easily accessible as are GPUs that deep learning frameworks ca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::defe6c39f8a91e09855c289bb9cc817d
https://doi.org/10.1109/dls49591.2019.00011
https://doi.org/10.1109/dls49591.2019.00011
Autor:
Chris A. Mattmann, Robert R. Downs, Ruth Duerr, Mike Folk, Jeff Dozier, James Frew, Nancy Hoebelheinrich, Ge Peng, Hampapuram Ramapriyan
Publikováno v:
Eos, vol 100
Author(s): Ramapriyan, Hampapuram; Downs, Robert; Dozier, Jeff; Duerr, Ruth; Folk, Mike; Frew, James; Hoebelheinrich, Nancy; Mattmann, Chris; Peng, Ge | Abstract: Bruce R. Barkstrom, principal investigator for NASA missions involved with understandin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::901328e5e8d565a36374106ad9a7c6ec
https://escholarship.org/uc/item/7979z47b
https://escholarship.org/uc/item/7979z47b