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Domain Informations
Network
- inetnum : 192.101.100.0 - 192.101.109.255
- name : PNNL
- handle : NET-192-101-100-0-1
- status : Direct Allocation
- created : 2010-02-16
- changed : 2022-07-12
Owner
- organization : Battelle Memorial Institute, Pacific Northwest Division
- handle : PNNL-Z
- address : Array,Richland,WA,99352,US
Technical support
- handle : SCT2-ARIN
- name : Tollbom, Cullen
- phone : +1-509-375-6703
- email : [email protected]
Abuse
- handle : LWA96-ARIN
- name : Allen, Lewis W
- phone : +1-509-375-3974
- email : [email protected]
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Host Informations
Host name | marine.pnnl.gov |
IP address | 192.101.105.83 |
Location | United States |
Latitude | 37.751 |
Longitude | -97.822 |
Timezone | America/Chicago |
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We found Websites Listing below when search with deeplearning.pnnl.gov on Search Engine
Artificial Intelligence | PNNL
Leveraging a deep expertise in the power grid domain, PNNL’s DeepGrid open-source platform uses deep reinforcement learning to help power system operators create more robust emergency control protocols—the safety net of our electric grid.
Deeplearning.pnnl.govDA: 21 PA: 21 MOZ Rank: 22
Using Deep Learning as a Searchlight for Dark Matter
Having run the deep learning model on data from a PICO bubble chamber at SNOLAB in Canada, the team is now building its own bubble chamber at PNNL, aiming to collect more data that can be used to train the …
Pnnl.govDA: 12 PA: 50 MOZ Rank: 68
PNNL: New Deep Learning Project Launches at PNNL
Advanced Computing, Mathematics and Data Research Highlights October 2016 New Deep Learning Project Launches at PNNL Recently, the U.S. Department of Energy’s Office of Advanced Scientific Computing Research awarded …
Pnnl.govDA: 12 PA: 33 MOZ Rank: 47
Deep Learning for Control with Embedded Physical …
Skip to main content. PNNL. About; News & Media; Careers; Events
Pnnl.govDA: 12 PA: 50 MOZ Rank: 88
Deep Learning Prediction of Interspecies Interactions …
Skip to main content. PNNL. About; News & Media; Careers; Events
Pnnl.govDA: 12 PA: 50 MOZ Rank: 46
pnnl/Deep-Learning-Control-with-Embedded-Physical …
Contribute to pnnl/Deep-Learning-Control-with-Embedded-Physical-Structure development by creating an account on GitHub.
Github.comDA: 10 PA: 50 MOZ Rank: 75
de novo peptide sequencing - Pacific Northwest National Laboratory
Molecular Science Laboratory, a DOE national scientific user facility at Pacific Northwest National Laboratory (PNNL) in Richland, WA. Battelle operates PNNL for the DOE under contract DE-AC05-76RLO01830. CONTACT: Joon-Yong Lee, Ph.D. Biological Sciences Division. Pacific Northwest National Laboratory. E-mail: [email protected]. Results
Panomics.pnnl.govDA: 17 PA: 50 MOZ Rank: 80
PNNL: Training Day - Pacific Northwest National Laboratory
The Deep Learning for Physical Sciences Workshop ’s aim was to unite members of the machine/deep learning and physical sciences communities to provide new approaches for solving physical science problems.
Pnnl.govDA: 12 PA: 33 MOZ Rank: 52
Using Deep Learning as a Searchlight for Dark Matter | PNNL
Scientists at PNNL are bringing artificial intelligence into the quest to see whether computers can help humans sift through a sea of experimental data. Using Deep Learning as a Searchlight for Dark Matter | PNNL
Beta11.pnnl.govDA: 15 PA: 50 MOZ Rank: 78
PNNL: News - Cloud or no cloud, that is the question
How deep learning is bringing automatic cloud detection to new heights Feature December 12, 2018 Susan Bauer, PNNL, (509) 372-6083 Download Original Image Clouds come in all shapes and sizes, and now a deep learning model can help detect the finer details in cloud data. Credit: Adriel Kloppenburg on Unsplash
Pnnl.govDA: 12 PA: 18 MOZ Rank: 39
Dr Peiyuan Gao | Datahub - data.pnnl.gov
(atomic to coarse-grained scale) Dr. Gao joined PNNL in 2016. He is involved in multiscale modeling of simple and complex fluids, electrolyte, and developing data-driven methods as machine learning and deep learning on molecular property prediction and design. He has published more than 30 peer-reviewed journal papers.
Data.pnnl.govDA: 13 PA: 13 MOZ Rank: 36
Physics-constrained Deep Learning of Building Thermal Dynamics
We presented a constrained deep learning method for sample-efficient and physics-consistent data-driven modeling of building thermal dynamics. Our approach does not require the large time investments by domain experts and extensive computational resources demanded by physics-based emulator models. Based on only 10 days’ measurements, we significantly …
Pnnl.github.ioDA: 14 PA: 50 MOZ Rank: 94
Svitlana (@svolkova) | Twitter
The latest Tweets from Svitlana (@svolkova). Scientist@PNNL. Richland, WA
Twitter.comDA: 11 PA: 9 MOZ Rank: 32
Generalized Block-Diagram Modeling of Power Electronic …
Partner with PNNL. Academia. Distinguished Graduate Research Programs; Internships ...
Beta11.pnnl.govDA: 15 PA: 50 MOZ Rank: 37
Echofilter: A Deep Learning Segmention Model Improves the …
Using a case study at a tidal energy demonstration site in the Bay of Fundy, we describe the development and application of deep machine learning models with a U-Net based architecture that produce a pronounced and substantial improvement in the automated detection of the extent to which entrained air has penetrated the water column.
Tethys.pnnl.govDA: 15 PA: 50 MOZ Rank: 36
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