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Št. zadetkov: 4
Podvajanje optične frekvence v feromagnetnih tekočih kristalih
Jure Brence, Irena Drevenšek Olenik
Magistrsko delo
Oznake: nelinearna optična susceptibilnost;podvajanje optične frekvence;nematski tekoči kristali;feromagnetni tekoči kristali;električno polje;magnetno polje;
Nematski tekoči kristali imajo v homogeni ureditvi centrosimetrično strukturo, zato podvajanje optične frekvence v njih ni mogoče. Zunanje električno polje centrosimetrijo poruši preko pojava električno inducirane polarizacije ter preko fleksoelektričnega pojava, ki je posledica reorientacije direkt ...
Leto: 2019 Vir: Fakulteta za matematiko in fiziko (UL FMF)
Dimensionally-consistent equation discovery through probabilistic attribute grammars
Jure Brence, Sašo Džeroski, Ljupčo Todorovski
Izvirni znanstveni članek
Oznake: equation discovery;symbolic regression;dimensional analysis;units of measurement;background information;computational scientific discovery;
Equation discovery, also known as symbolic regression, is a machine learning task of inducing closed-form equations from data and background knowledge. The latter takes various forms. Domain-specific knowledge can constrain the space of candidate equations to those that make sense in the scientific ...
Leto: 2023 Vir: Fakulteta za matematiko in fiziko (UL FMF)
Probabilistic grammars for modeling dynamical systems from coarse, noisy, and partial data
Nina Omejc, Boštjan Gec, Jure Brence, Ljupčo Todorovski, Sašo Džeroski
Izvirni znanstveni članek
Oznake: odkrivanje enačb;ordinary differential equations;equation discovery;mathematical modeling;system identification;symbolic regression;partial observability;
Ordinary differential equations (ODEs) are a widely used formalism for the mathematical modeling of dynamical systems, a task omnipresent in scientific domains. The paper introduces a novel method for inferring ODEs from data, which extends ProGED, a method for equation discovery that allows users t ...
Leto: 2024 Vir: Fakulteta za matematiko in fiziko (UL FMF)
Predictions of failed satellite retrieval of air quality using machine learning
Edward Malina, Jure Brence, Jennifer Adams, Jovan Tanevski, Sašo Džeroski, Valentin Kantchev, Kevin W. Bowman
Izvirni znanstveni članek
Oznake: plini v sledovih;zaznavanje napak;napovedovanje napak;trace gases;failure prediction;
The growing fleet of Earth observation (EO) satellites is capturing unprecedented quantities of information about the concentration and distribution of trace gases in the Earth's atmosphere. Depending on the instrument and algorithm, the yield of good remote soundings can be a few percent owing to i ...
Leto: 2025 Vir: Institut Jožef Stefan (IJS)
Št. zadetkov: 4
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