Latent variables
Disambiguating Latent Variables
... Latent variables are ubiquitous in the social and behavioral ...between variables that are manifest and variables that are ...Manifest variables are, at first pass, distinguished by ...
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Variational inference for latent variables and uncertain inputs in Gaussian processes
... temporal latent function for each of the independent sequences, so that X (i) is the set of latent variables corresponding to the sequence ...
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Modeling Semantic Relationship in Multi turn Conversations with Hierarchical Latent Variables
... hierarchical latent variables based on VAEs to represent the meaning of utterances and meanwhile learns the relationship between query and ...discourse-level latent variable and then models the ...
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Zero shot Cross lingual Dialogue Systems with Transferable Latent Variables
... transferable latent variable that focuses on improving the zero-shot cross-lingual adaptation of natural language un- derstanding task to low-resource ...3) latent variables are effective in coping ...
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The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models
... underlying latent variables (UVs) to ...continuous variables can be constructed by using the identity link function instead of probit for the continuous ...continuous variables will not nec- ...
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Three-way interactions with latent variables : a maximum likelihood approach
... in latent variables has been a topic of considerable theoret- ical and practical interest among psychological ...of latent moderation ...nonlinear latent variables models provided a new ...
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Variational Inference for Latent Variables and Uncertain Inputs in Gaussian Processes
... In the next subsection we summarise the notation and conventions used in this paper. In Section 2 we review the main prior work on dealing with latent variables in the context of Gaussian processes and ...
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Doc2hash: Learning Discrete Latent variables for Documents Retrieval
... log h k i ). similar relaxation techniques have been introduced as the Gumbel-Softmax trick in (Jang et al., 2016; Maddison et al., 2016). Since Eq. 8 is differentiable, we can train the generative model in an end-to-end ...
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Piecewise Latent Variables for Neural Variational Text Processing
... the latent variables in VAEs, such as autoregressive distributions, hierarchical prob- abilistic models and approximations based on MCMC sampling (Rezende et ...discrete latent variables ...
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Learning Linear Cyclic Causal Models with Latent Variables
... In this contribution we consider the problem of learning the structure and parameters of linear cyclic causal models from equilibrium data. We derive a necessary and sufficient condition for identifiability based on ...
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Predicting gender differences as latent variables: summed scores, and individual item responses: a methods case study
... between latent variables and ...of latent variables measured as summed scores using linear regression models, prediction of individual item responses using logistic regression models and pro- ...
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Spatio-temporal Bayesian network models with latent variables for revealing trophic dynamics and functional networks in fisheries ecology
... Next, we further improved the HDBN by allowing for spatial auto- correlation and learning another dynamic BN model: HSDBN. Similarly to HDBN, the HSDBN structure represents a potential “ end-to-end ” eco- system model of ...
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Using latent variables in logistic regression to reduce multicollinearity, A case-control example: breast cancer risk factors
... of latent variables for data reduction actually has had more application in psychology and social sciences [5], but because of some conditions in the areas of epidemiology and medical sciences which ...
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Geographically Weighted Structural Equation Models: understanding the spatial variation of latent variables and drivers of environmental restoration effectiveness
... and latent model ...or latent variables. To handle this a series of latent equations are used to generate parameters that are passed to regression operations and residual correlation ...three ...
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Measuring Set Latent Variables Through Exploratory Factor Analysis with Principal Components Extraction and Validation with AMOS Software
... Regarding discriminant validity, the values shown in Table 14 reveal that all are less than 1; hence, none of the items were part of the different factors, shown in the other constructs. Thompson (2004) refers that ...
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Structural equation modeling with latent variables for longitudinal blood pressure traits using general pedigrees
... and latent growth curve (LG) ...a latent variable that affects both SBP and DBP in both ...the latent variables at different time points and the SNP effect on the underlying latent ...
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Latent variables and structural equation models for longitudinal relationships: an illustration in nutritional epidemiology
... adiposity latent variable within a structural model avoids the draw- backs of either arbitrarily choosing a single adiposity measurement or performing separate analyses on each fat-mass ...considering ...
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Some Recent Advances in Non- and Semiparametric Bayesian Modeling with Copulas, Mixtures, and Latent Variables
... cially damaging. The copula correlation between GDPW and black market premium (on which the data are most informative) is underestimated in the Gaussian/probit model: mean −0.33 and 95% HPD interval (−0.46, −0.22) as ...
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Improved Learning Of Structural Support Vector Machines: Training With Latent Variables And Nonlinear Kernels
... involves latent or missing information and is very com- mon in natural language processing and computer ...of latent variables and an efficient algorithm to solve the associated training ...
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Probabilistic Tree Edit Models with Structured Latent Variables for Textual Entailment and Question Answering
... textual support (i.e., does not merely contain the answer key, for example, ”Ingemar Johansson was a world heavyweight champion” would not be a correct answer). We followed the same ex- perimental setup as Wang et al. ...
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