FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2955651397> ?p ?o ?g. }

• W2955651397 endingPage "107402" @default.
• W2955651397 startingPage "107402" @default.
• W2955651397 abstract "Prediction of material properties from first principles is often a computationally expensive task. Recently, artificial neural networks and other machine learning approaches have been successfully employed to obtain accurate models at a low computational cost by leveraging existing example data. Here, we present a software package Properties from Artificial Neural Network Architectures (PANNA) that provides a comprehensive toolkit for creating neural network models for atomistic systems. Besides the core routines for neural network training, it includes data parser, descriptor builder and force-field generator suitable for integration within molecular dynamics packages. PANNA offers a variety of activation and cost functions, regularization methods, as well as the possibility of using fully-connected networks with custom size for each atomic species. PANNA benefits from the optimization and hardware-flexibility of the underlying TensorFlow engine which allows it to be used on multiple CPU/GPU/TPU systems, making it possible to develop and optimize neural network models based on large datasets." @default.
• W2955651397 created "2019-07-12" @default.
• W2955651397 creator A5009574969 @default.
• W2955651397 creator A5026935407 @default.
• W2955651397 creator A5058592328 @default.
• W2955651397 creator A5078475792 @default.
• W2955651397 date "2020-11-01" @default.
• W2955651397 modified "2023-10-18" @default.
• W2955651397 title "PANNA: Properties from Artificial Neural Network Architectures" @default.
• W2955651397 cites W1531674615 @default.
• W2955651397 cites W1970303695 @default.
• W2955651397 cites W1975997599 @default.
• W2955651397 cites W2019465613 @default.
• W2955651397 cites W2025444507 @default.
• W2955651397 cites W2029413789 @default.
• W2955651397 cites W2030613443 @default.
• W2955651397 cites W2030976617 @default.
• W2955651397 cites W2034097448 @default.
• W2955651397 cites W2037782625 @default.
• W2955651397 cites W2043701535 @default.
• W2955651397 cites W2057858097 @default.
• W2955651397 cites W2061179540 @default.
• W2955651397 cites W2064690388 @default.
• W2955651397 cites W2083222334 @default.
• W2955651397 cites W2083415705 @default.
• W2955651397 cites W2093307998 @default.
• W2955651397 cites W2104489082 @default.
• W2955651397 cites W2200589053 @default.
• W2955651397 cites W2206840988 @default.
• W2955651397 cites W2315586250 @default.
• W2955651397 cites W2335163884 @default.
• W2955651397 cites W2410722695 @default.
• W2955651397 cites W2509907061 @default.
• W2955651397 cites W2541404351 @default.
• W2955651397 cites W2551377153 @default.
• W2955651397 cites W2566573083 @default.
• W2955651397 cites W2593838212 @default.
• W2955651397 cites W2742127985 @default.
• W2955651397 cites W2764267192 @default.
• W2955651397 cites W2766856748 @default.
• W2955651397 cites W2768213699 @default.
• W2955651397 cites W2771888471 @default.
• W2955651397 cites W2775708988 @default.
• W2955651397 cites W2776192919 @default.
• W2955651397 cites W2778051509 @default.
• W2955651397 cites W2792407267 @default.
• W2955651397 cites W2800168263 @default.
• W2955651397 cites W2804030504 @default.
• W2955651397 cites W2806393871 @default.
• W2955651397 cites W2885841934 @default.
• W2955651397 cites W2885918708 @default.
• W2955651397 cites W2889703828 @default.
• W2955651397 cites W2894355378 @default.
• W2955651397 cites W2904141086 @default.
• W2955651397 cites W2911490414 @default.
• W2955651397 cites W2914218087 @default.
• W2955651397 cites W2923693308 @default.
• W2955651397 cites W2944649260 @default.
• W2955651397 cites W2950090532 @default.
• W2955651397 cites W2964015639 @default.
• W2955651397 cites W3098370560 @default.
• W2955651397 cites W3098472025 @default.
• W2955651397 cites W3099950071 @default.
• W2955651397 cites W3102380997 @default.
• W2955651397 cites W3102449990 @default.
• W2955651397 doi "https://doi.org/10.1016/j.cpc.2020.107402" @default.
• W2955651397 hasPublicationYear "2020" @default.
• W2955651397 type Work @default.
• W2955651397 sameAs 2955651397 @default.
• W2955651397 citedByCount "31" @default.
• W2955651397 countsByYear W29556513972019 @default.
• W2955651397 countsByYear W29556513972020 @default.
• W2955651397 countsByYear W29556513972021 @default.
• W2955651397 countsByYear W29556513972022 @default.
• W2955651397 countsByYear W29556513972023 @default.
• W2955651397 crossrefType "journal-article" @default.
• W2955651397 hasAuthorship W2955651397A5009574969 @default.
• W2955651397 hasAuthorship W2955651397A5026935407 @default.
• W2955651397 hasAuthorship W2955651397A5058592328 @default.
• W2955651397 hasAuthorship W2955651397A5078475792 @default.
• W2955651397 hasBestOaLocation W29556513971 @default.
• W2955651397 hasConcept C105795698 @default.
• W2955651397 hasConcept C118524514 @default.
• W2955651397 hasConcept C119857082 @default.
• W2955651397 hasConcept C154945302 @default.
• W2955651397 hasConcept C199360897 @default.
• W2955651397 hasConcept C202444582 @default.
• W2955651397 hasConcept C2777904410 @default.
• W2955651397 hasConcept C2780598303 @default.
• W2955651397 hasConcept C33923547 @default.
• W2955651397 hasConcept C41008148 @default.
• W2955651397 hasConcept C50644808 @default.
• W2955651397 hasConcept C9652623 @default.
• W2955651397 hasConceptScore W2955651397C105795698 @default.
• W2955651397 hasConceptScore W2955651397C118524514 @default.
• W2955651397 hasConceptScore W2955651397C119857082 @default.
• W2955651397 hasConceptScore W2955651397C154945302 @default.
• W2955651397 hasConceptScore W2955651397C199360897 @default.

• next