Piecewise Latent Variables for Neural Variational Text Processing
Conference on Empirical Methods in Natural Language Processing, 2017 Advances in neural variational inference have facilitated the learning of powerful directed graphical models with continuous latent variables, such as variational autoencoders. The hope is that such models will learn to represent rich, multi-modal latent
Courville, Aaron +3 more
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Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation [PDF]
Neural Information Processing Systems, 2023 We tackle the problems of latent variables identification and ``out-of-support'' image generation in representation learning. We show that both are possible for a class of decoders that we call additive, which are reminiscent of decoders used for object ...
Sébastien Lachapelle +3 more
semanticscholar +1 more source
GLAT: Glancing at Latent Variables for Parallel Text Generation [PDF]
Annual Meeting of the Association for Computational Linguistics, 2022 Recently, parallel text generation has received widespread attention due to its success in generation efficiency. Although many advanced techniques are proposed to improve its generation quality, they still need the help of an autoregressive model for ...
Yu Bao +7 more
semanticscholar +1 more source
High dimensional mediation analysis with latent variables. [PDF]
Biometrics, 2019 We propose a model for high dimensional mediation analysis that includes latent variables. We describe our model in the context of an epidemiologic study for incident breast cancer with one exposure and a large number of biomarkers (i.e., potential ...
Derkach A +3 more
europepmc +2 more sources
A review of dynamic network models with latent variables. [PDF]
Stat Surv, 2018 We present a selective review of statistical modeling of dynamic networks. We focus on models with latent variables, specifically, the latent space models and the latent class models (or stochastic blockmodels), which investigate both the observed ...
Kim B, Lee KH, Xue L, Niu X.
europepmc +3 more sources
Squaring the circle: From latent variables to theory-based measurement
Theory & Psychology, 2022 Psychometrics builds on the fundamental premise that psychological attributes are unobservable and need to be inferred from observable behavior.
Matthias Borgstede, F. Eggert
semanticscholar +1 more source
Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders [PDF]
, 2021 Random effect models are popular statistical models for detecting and correcting spurious sample correlations due to hidden confounders in genome-wide gene expression data.
Malik, Muhammad Ammar, Michoel, Tom
core +2 more sources
Exploring the latent variables which support SMEs to become learning organizations
Management & Marketing. Challenges for the Knowledge Society, 2020 The purpose of this paper is to explore the latent variables which support small and medium-sized enterprises (SMEs) in becoming learning organizations.
C. Bratianu +2 more
semanticscholar +1 more source
Diversifying Emotional Dialogue Generation via Selective Adversarial Training
Sensors, 2023 Emotional perception and expression are very important for building intelligent conversational systems that are human-like and attractive. Although deep neural approaches have made great progress in the field of conversation generation, there is still a ...
Bo Li, Huan Zhao, Zixing Zhang
doaj +1 more source
Modeling Psychological Attributes in Psychology - An Epistemological Discussion: Network Analysis vs. Latent Variables. [PDF]
Front Psychol, 2017 Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any ...
Guyon H, Falissard B, Kop JL.
europepmc +2 more sources