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DBN Group
DBN may refer to: * 1,5-Diazabicyclo(4.3.0)non-5-ene, a chemical * DBN1, a human gene * Deep belief network, type of neural network * Dynamic Bayesian network A Dynamic Bayesian Network (DBN) is a Bayesian network (BN) which relates variables to each other over adjacent time steps. This is often called a ''Two-Timeslice'' BN (2TBN) because it says that at any point in time T, the value of a variable c ..., a statistical model * DBN (band), a German trio {{disambiguation ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Please Do Not Bite The Newcomers
''Please'' is a word used in the English language to indicate politeness and respect while making a request. Derived from shortening the phrase "if you please" or "if it please(s) you", the term has taken on substantial nuance based on its intonation and the relationship between the persons between whom it is used. In much of the Western world, use of the word is considered proper etiquette, and parents and authority figures often imprint upon children the importance of saying "please" when asking for something from an early age, leading to the description of the term as "the magic word". Origin and understanding "Please" is a shortening of the phrase, ''if you please'', an intransitive, ergative form taken from ''if it please you'', which is in turn a calque of the French ''s'il vous plaît'', which replaced ''pray''. The exact time frame of the shortening is unknown, though it has been noted that this form appears not to have been known to William Shakespeare, for whom "ple ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
DBN1
Drebrin is a protein that in humans is encoded by the ''DBN1'' gene. The protein encoded by this gene is a cytoplasmic actin-binding protein thought to play a role in the process of neuronal growth. It is a member of the drebrin family of proteins that are developmentally regulated in the brain. A decrease in the amount of this protein in the brain has been implicated as a possible contributing factor in the pathogenesis of memory disturbance in Alzheimer's disease. At least two alternative splice variants encoding different protein isoforms have been described for this gene. Model organisms Model organisms have been used in the study of DBN1 function. A conditional knockout mouse line called ''Dbn1tm1b(KOMP)Wtsi'' was generated at the Wellcome Trust Sanger Institute. Male and female animals underwent a standardized phenotypic screen In genetics, the phenotype () is the set of observable characteristics or traits of an organism. The term covers the organism's morphology o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Deep Belief Network
In machine learning, a deep belief network (DBN) is a generative graphical model, or alternatively a class of deep neural network, composed of multiple layers of latent variables ("hidden units"), with connections between the layers but not between units within each layer. When trained on a set of examples without supervision, a DBN can learn to probabilistically reconstruct its inputs. The layers then act as feature detectors. After this learning step, a DBN can be further trained with supervision to perform classification. DBNs can be viewed as a composition of simple, unsupervised networks such as restricted Boltzmann machines (RBMs) or autoencoders, where each sub-network's hidden layer serves as the visible layer for the next. An RBM is an undirected, generative energy-based model with a "visible" input layer and a hidden layer and connections between but not within layers. This composition leads to a fast, layer-by-layer unsupervised training procedure, where contrastiv ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dynamic Bayesian Network
A Dynamic Bayesian Network (DBN) is a Bayesian network (BN) which relates variables to each other over adjacent time steps. This is often called a ''Two-Timeslice'' BN (2TBN) because it says that at any point in time T, the value of a variable can be calculated from the internal regressors and the immediate prior value (time T-1). DBNs were developed by Paul Dagum in the early 1990s at Stanford University's Section on Medical Informatics. Dagum developed DBNs to unify and extend traditional linear state-space models such as Kalman filters, linear and normal forecasting models such as ARMA and simple dependency models such as hidden Markov models into a general probabilistic representation and inference mechanism for arbitrary nonlinear and non-normal time-dependent domains. Today, DBNs are common in robotics, and have shown potential for a wide range of data mining applications. For example, they have been used in speech recognition, digital forensics, protein sequencing, an ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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