I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Discovering Novel Pharmaceutical Molecules with Generative ..:
, In:
2023 10th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)
,
Chandrashekar, Leena
;
K, Namratha
;
Mohan, Padmapriya
.. - p. 378-383 , 2023
Link:
https://doi.org/10.1109/EECSI59885.2023.10295896
RT T1 <cTitle>2023 10th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)</cTitle>: T1 <Title>Discovering Novel Pharmaceutical Molecules with Generative Adversarial Networks</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10295896&Exemplar=1&LAN=DE A1 Chandrashekar, Leena A1 K, Namratha A1 Mohan, Padmapriya A1 P J, Raxna Bopanna A1 Kulkarni, Aditi YR 2023 K1 Drugs K1 Deep learning K1 Proteins K1 Recurrent neural networks K1 Pipelines K1 Reinforcement learning K1 Generative adversarial networks K1 pharmaceutical molecule design K1 neural network K1 computer aided-drug design K1 Generative Adversarial Networks K1 Validity SP 378 OP 383 LK http://dx.doi.org/https://doi.org/10.1109/EECSI59885.2023.10295896 DO https://doi.org/10.1109/EECSI59885.2023.10295896 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
