Tools

LEADER 02786nam 2200517 i 4500

001 on1534150187;

005 20250822151609.0;

006 m o d f ;

007 cr |||||||||||;

008 250822s2023 dcuad ob f100 0 eng c;

035 a| (Sirsi) o1534150187;

035 a| (OCoLC)1534150187;

042 a| pcc;

043 a| n-us---;

049 a| ERE#;

074 a| 0430-Q (online);

086 0 a| E 10.2:AR 3;

088 a| DOE/SC-0211;

111 2 a| Artificial Intelligence and Machine Learning for Bioenergy Research: Workshop on Opportunities and Challengesd| (2022 :c| Online),j| author.0| http://id.loc.gov/authorities/names/no2025092127=| ^A1484649;

245 10 a| Artificial intelligence and machine learning for bioenergy research :b| opportunities and challenges.;

264 1 a| Washington, D.C. :b| U.S. Department of Energy, Office of Science, Office of Energy Efficiency and Renewable Energy,c| 2023.;

300 a| 1 online resource (iv, 49 pages) :b| color illustrations;

336 a| textb| txt2| rdacontent;

337 a| computerb| c2| rdamedia;

338 a| online resourceb| cr2| rdacarrier;

500 a| "DOE/SC-0211.";

500 a| "April 2023.";

500 a| "The U.S. Department of Energy's (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23-25, 2022";

500 a| In scope of the U.S. Government Publishing Office Cataloging and Indexing Program (C&I) and Federal Depository Library Program (FDLP).;

504 a| Includes bibliographical references (pages 46-48).;

588 a| Description based on online resource; title from PDF title page (DOE, viewed April 18, 2025).;

655 7 a| Conference papers and proceedings.2| lcgft0| http://id.loc.gov/authorities/genreForms/gf2014026068;

856 40 u| https://purl.fdlp.gov/GPO/gpo2454557| 0;

856 4 z| Address at time of PURL creationu| https://genomicscience.energy.gov/amber-ai-ml/;

949 a| Click on web addressw| asish| joyner94o| jjlm;

994 a| C0b| GPO;

955 a| bc108 20250822b| 20250822;

922 a| BIBCONEWb| 20250822;

596 a| 1;

998 a| 6616048;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 6616048-1001l| JNETm| JOYNERr| Ys| Yt| JNE1DOu| 9/19/2025x| EDOCUMENTz| JERESOURCEo| .STAFF. jjlm;

Artificial intelligence and machine learning for bioenergy research : opportunities and challenges.

Author/creator	Artificial Intelligence and Machine Learning for Bioenergy Research: Workshop on Opportunities and Challenges
Other author	United States. Department of Energy. Office of Energy Efficiency and Renewable Energy, issuing body.
Format	Electronic
Publication	Washington, D.C. : U.S. Department of Energy, Office of Science, Office of Energy Efficiency and Renewable Energy, 2023.
Description	1 online resource (iv, 49 pages) : color illustrations
Supplemental Content	https://purl.fdlp.gov/GPO/gpo245455
Supplemental Content	Address at time of PURL creation
Subjects	Artificial intelligence--Research. --United States. --Congresses. Machine learning--Research. --United States. --Congresses. Biomass energy--Research. --United States. --Congresses.

General note	"DOE/SC-0211."
General note	"April 2023."
General note	"The U.S. Department of Energy's (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23-25, 2022"
General note	In scope of the U.S. Government Publishing Office Cataloging and Indexing Program (C&I) and Federal Depository Library Program (FDLP).
Bibliography note	Includes bibliographical references (pages 46-48).
Source of description	Description based on online resource; title from PDF title page (DOE, viewed April 18, 2025).
Genre/form	Conference papers and proceedings.
Technical rpt number	DOE/SC-0211
GPO item number	0430-Q (online)
Govt. docs number	E 10.2:AR 3

Artificial intelligence and machine learning for bioenergy research : opportunities and challenges.

Click here for more information about this title