Literatura científica selecionada sobre o tema "Modèle latent"
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Artigos de revistas sobre o assunto "Modèle latent"
Cialdella, P., O. Chambon, J. P. Boissel e E. Ravet-Cialdella. "La recherche d’une mesure unidimensionnelle de la dépression: à propos de l’échelle de dépression de Hamilton". Psychiatry and Psychobiology 4, n.º 4 (1989): 203–10. http://dx.doi.org/10.1017/s0767399x00002765.
Texto completo da fonteKorahiré, Joël Awouhidia. "Dynamiques socioéconomiques dans les villages riverains au ranch de gibier de Nazinga au Burkina Faso". Articles 40, n.º 2 (24 de março de 2011): 53–70. http://dx.doi.org/10.7202/1001388ar.
Texto completo da fonteDescheneau-Guay, Amélie. "Les séries jeunesse et les stéréotypes sexuels : la récupération de l’idée d’émancipation et l’émergence d’une culture du consensus". Notes de recherche 19, n.º 2 (21 de março de 2007): 143–54. http://dx.doi.org/10.7202/014846ar.
Texto completo da fonteChilds, Ruth A., Orlena Broomes e Monique B. Herbert. "Deciding Whether to Respond: A Latent Class Analysis of Nonresponse on Ontario’s Grade 9 Assessment of Mathematics". Alberta Journal of Educational Research 64, n.º 1 (2 de maio de 2018): 70–87. http://dx.doi.org/10.55016/ojs/ajer.v64i1.56472.
Texto completo da fonteBurton, Réginald. "Influence des distributions du trait latent et de la difficulté des items sur les estimations du modèle de Birnbaum : une étude du type Monte-Carlo". Mesure et évaluation en éducation 27, n.º 3 (2004): 41. http://dx.doi.org/10.7202/1087787ar.
Texto completo da fonteNyambiya, T. E., T. Muromo e K. Muchena. "‘My blood is now old and exhausted’: A Qualitative Study of Adults’ Behavioural Beliefs About Donating Blood in Harare, Zimbabwe". Africa Sanguine 22, n.º 1 (25 de maio de 2020): 14–22. http://dx.doi.org/10.4314/asan.v22i1.3.
Texto completo da fonteFine, David. "Nursing’s latest module". Nursing Standard 6, n.º 23 (26 de fevereiro de 1992): 51. http://dx.doi.org/10.7748/ns.6.23.51.s53.
Texto completo da fonteChaudhary, Neha, e Priti Dimri. "LATENT FINGERPRINT IMAGE ENHANCEMENT BASED ON OPTIMIZED BENT IDENTITY BASED CONVOLUTIONAL NEURAL NETWORK". Indian Journal of Computer Science and Engineering 12, n.º 5 (20 de outubro de 2021): 1477–93. http://dx.doi.org/10.21817/indjcse/2021/v12i5/211205124.
Texto completo da fonteChen, Fangdong, Yumeng Xu e Li Wang. "Two-Stage Octave Residual Network for End-to-End Image Compression". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 4 (28 de junho de 2022): 3922–29. http://dx.doi.org/10.1609/aaai.v36i4.20308.
Texto completo da fonteJin Dai, Jin Dai, e Zhifang Zheng Jin Dai. "Disentangling Representation of Variational Autoencoders Based on Cloud Models". 電腦學刊 34, n.º 6 (dezembro de 2023): 001–14. http://dx.doi.org/10.53106/199115992023123406001.
Texto completo da fonteTeses / dissertações sobre o assunto "Modèle latent"
Brault, Vincent. "Estimation et sélection de modèle pour le modèle des blocs latents". Thesis, Paris 11, 2014. http://www.theses.fr/2014PA112238/document.
Texto completo da fonteClassification aims at sharing data sets in homogeneous subsets; the observations in a class are more similar than the observations of other classes. The problem is compounded when the statistician wants to obtain a cross classification on the individuals and the variables. The latent block model uses a law for each crossing object class and class variables, and observations are assumed to be independent conditionally on the choice of these classes. However, factorizing the joint distribution of the labels is impossible, obstructing the calculation of the log-likelihood and the using of the EM algorithm. Several methods and criteria exist to find these partitions, some frequentist ones, some bayesian ones, some stochastic ones... In this thesis, we first proposed sufficient conditions to obtain the identifiability of the model. In a second step, we studied two proposed algorithms to counteract the problem of the EM algorithm: the VEM algorithm (Govaert and Nadif (2008)) and the SEM-Gibbs algorithm (Keribin, Celeux and Govaert (2010)). In particular, we analyzed the combination of both and highlighted why the algorithms degenerate (term used to say that it returns empty classes). By choosing priors wise, we then proposed a Bayesian adaptation to limit this phenomenon. In particular, we used a Gibbs sampler and we proposed a stopping criterion based on the statistics of Brooks-Gelman (1998). We also proposed an adaptation of the Largest Gaps algorithm (Channarond et al. (2012)). By taking their demonstrations, we have shown that the labels and parameters estimators obtained are consistent when the number of rows and columns tend to infinity. Furthermore, we proposed a method to select the number of classes in row and column, the estimation provided is also consistent when the number of row and column is very large. To estimate the number of classes, we studied the ICL criterion (Integrated Completed Likelihood) whose we proposed an exact shape. After studying the asymptotic approximation, we proposed a BIC criterion (Bayesian Information Criterion) and we conjecture that the two criteria select the same results and these estimates are consistent; conjecture supported by theoretical and empirical results. Finally, we compared the different combinations and proposed a methodology for co-clustering
Mura, Thibault. "Prévention des démences : analyse du déclin cognitif à l’aide d’un modèle longitudinal non linéaire à variable latente". Thesis, Montpellier 1, 2012. http://www.theses.fr/2012MON1T018/document.
Texto completo da fonteThe first aim of this doctoral work is to replace dementia in its public health context by estimating the number of dementia cases expected to occur in France and Europe over the next few decades until 2050. The sensitivity of these projections to hypotheses made on dementia incidence and mortality, demographic scenario used, and implementation of a prevention intervention, was also assessed. In this context of increasing number of future cases, the primary and secondary prevention of dementia will take a prominent place in the social management of this problem. Relevant research in the field of primary and secondary prevention requires an appropriate methodology and the use of relevant outcome. Cognitive decline seems to be an appropriate outcome, but a number of biases must be avoided. First, we illustrated the use of this criterion in the context of primary prevention using a nonlinear model with latent variable for longitudinal data to investigated the association between chronic use of benzodiazepines and cognitive decline. We showed the absence of association in a large population-based cohort. Secondly we used this model to describe and compare the metrological properties of a broad range of neuropsychological tests in a clinical cohort of patients with mild cognitive impairment (MCI). We also investigated the sensitivity of these tests to cognitive changes associated with prodromal Alzheimer's disease. Our work provides arguments for selecting neuropsychological tests which can be used in secondary prevention research, to identify and / or to follow patients with mild cognitive impairment (MCI) due to Alzheimer's disease
Samuth, Benjamin. "Ηybrid mοdels cοmbining deep neural representatiοns and nοn-parametric patch-based methοds fοr phοtοrealistic image generatiοn". Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMC249.
Texto completo da fonteImage generation has encountered great progress thanks to the quickevolution of deep neural models. Their reach went beyond thescientific domain and thus multiple legitimate concerns and questionshave been raised, in particular about how the training data aretreated. On the opposite, lightweight and explainable models wouldbe a fitting answer to these emerging problematics, but their qualityand range of applications are limited.This thesis strives to build “hybrid models”. They would efficientlycombine the qualities of lightweight or frugal methods with theperformance of deep networks. We first study the case of artisticstyle transfer with a multiscale and constrained patch-basedmethod. We qualitatively find out the potential of perceptual metricsin the process. Besides, we develop two hybrid models forphotorealistic face generation, each built around a pretrainedauto-encoder. The first model tackles the problem of few-shot facegeneration with the help of latent patches. Results shows a notablerobustness and convincing synthesis with a simple patch-basedsequential algorithm. The second model uses Gaussian mixtures modelsas a way to generalize the previous method to wider varieties offaces. In particular, we show that these models perform similarly toother neural methods, while removing a non-negligible number ofparameters and computing steps at the same time
Dantan, Etienne. "Modèles conjoints pour données longitudinales et données de survie incomplètes appliqués à l'étude du vieillissement cognitif". Thesis, Bordeaux 2, 2009. http://www.theses.fr/2009BOR21658/document.
Texto completo da fonteIn cognitive ageing study, older people are highly selected by a risk of death associated with poor cognitive performances. Modeling the natural history of cognitive decline is difficult in presence of incomplete longitudinal and survival data. Moreover, the non observed cognitive decline acceleration beginning before the dementia diagnosis is difficult to evaluate. Cognitive decline is highly heterogeneous, e.g. there are various patterns associated with different risks of survival event. The objective is to study joint models for incomplete longitudinal and survival data to describe the cognitive evolution in older people. Latent variable approaches were used to take into account the non-observed mechanisms, e.g. heterogeneity and decline acceleration. First, we compared two approaches to consider missing data in longitudinal data analysis. Second, we propose a joint model with a latent state to model cognitive evolution and its pre-dementia acceleration, dementia risk and death risk
Robert, Valérie. "Classification croisée pour l'analyse de bases de données de grandes dimensions de pharmacovigilance". Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS111/document.
Texto completo da fonteThis thesis gathers methodological contributions to the statistical analysis of large datasets in pharmacovigilance. The pharmacovigilance datasets produce sparse and large matrices and these two characteritics are the main statistical challenges for modelling them. The first part of the thesis is dedicated to the coclustering of the pharmacovigilance contingency table thanks to the normalized Poisson latent block model. The objective is on the one hand, to provide pharmacologists with some interesting and reduced areas to explore more precisely. On the other hand, this coclustering remains a useful background information for dealing with individual database. Within this framework, a parameter estimation procedure for this model is detailed and objective model selection criteria are developed to choose the best fit model. Datasets are so large that we propose a procedure to explore the model space in coclustering, in a non exhaustive way but a relevant one. Additionnally, to assess the performances of the methods, a convenient coclustering index is developed to compare partitions with high numbers of clusters. The developments of these statistical tools are not specific to pharmacovigilance and can be used for any coclustering issue. The second part of the thesis is devoted to the statistical analysis of the large individual data, which are more numerous but also provides even more valuable information. The aim is to produce individual clusters according their drug profiles and subgroups of drugs and adverse effects with possible links, which overcomes the coprescription and masking phenomenons, common contingency table issues in pharmacovigilance. Moreover, the interaction between several adverse effects is taken into account. For this purpose, we propose a new model, the multiple latent block model which enables to cocluster two binary tables by imposing the same row ranking. Assertions inherent to the model are discussed and sufficient identifiability conditions for the model are presented. Then a parameter estimation algorithm is studied and objective model selection criteria are developed. Moreover, a numeric simulation model of the individual data is proposed to compare existing methods and study its limits. Finally, the proposed methodology to deal with individual pharmacovigilance data is presented and applied to a sample of the French pharmacovigilance database between 2002 and 2010
Georgescu, Vera. "Classification de données multivariées multitypes basée sur des modèles de mélange : application à l'étude d'assemblages d'espèces en écologie". Phd thesis, Université d'Avignon, 2010. http://tel.archives-ouvertes.fr/tel-00624382.
Texto completo da fonteArzamendia, Lopez Juan Pablo. "Métholodogie de conception des matériaux architecturés pour le stockage latent dans le domaine du bâtiment". Thesis, Lyon, INSA, 2013. http://www.theses.fr/2013ISAL0060/document.
Texto completo da fonteThe use of energy storage systems that exploit latent heat represents a promising solution to erase the heating demand of residential buildings during periods of peak demand. Equipping a building with such components can contribute to the goal of peak shaving in terms of public electricity grid supply. Significant drawbacks, however, are the low thermal conductivity of Phase Change Materials (PCM) that typically constitute such systems,and the requirement for a high rate of discharge. Consequently, the use of so-called architectured materials has been put forward as a means to optimize the effective conductivity of storage materials. Our work is focused upon the development of a methodology to design optimal materials for such systems that meet the criteria of energy storage and energy output. A so-called “top-down metholodogy” was implemented for the present work. This approach includes three scales of interest: building (top), system and material (down). The aim of the building scale analysis is to formulate a set of general design requirements. These are complemented by performance indicators, which are defined at the scale of the system. Finally, at the scale of the material, the architecture of the identified material is elaborated. A numerical simulation tool was developed to determine performance indicators for a latent heat energy storage system comprising of an air/PCM heat exchanger. This model was tested against a benchmark analytical solution and validated though comparison to experimental data. The developed methodology is applied to the specific case of an air/PCM exchanger latent-heat energy storage system. The system is analysed through the study of dimensionless numbers, which provide a set of design indicators for the system. As a result of this stage, the optimal material and functional properties are thus identified. Finally, an architectured material is proposed that would satisfy the design requirements of the storage system. We demonstrate that an arrangement composed of a sandwich of planar layers with nails and PCM can offer the required material properties. Furthermore, in order to meet the desired functional properties, the system design is modified by the addition of fins at the exchange surfaces. With the addition of 20 fins of 3mm thickness attached to the exchange surface of the sandwich panel, the storage system eliminated the heating demand for 2 hours during the period of high daily demand in winter
Diallo, Alhassane. "Recherche de sous-groupes évolutifs et leur impact sur la survie : application à des patients atteints d'ataxie spinocérébelleuse (SCA) Body Mass Index Decline Is Related to Spinocerebellar Ataxia Disease Progression Survival in patients with spinocerebellar ataxia types 1, 2, 3, and 6 (EUROSCA): a longitudinal cohort study". Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS447.
Texto completo da fonteIn cohort studies, most often the models used assume that the study population follows an average pattern of evolution. However, in many cases, such as for spinocerebellar ataxias (SCA), it is not uncommon for heterogeneity to be suspected. This heterogeneity could also be inuenced by other intercurrent events for example joint evolution of a second phenotype or occurrence of an event such as dropout or death. In the first part of this thesis, we analyzed the evolution of the BMI of SCA patients and looked for different evolution profiles of BMI. We identified 3 subgroups of BMI evolution: decrease (23% of patients), increase (18%) and stable (59%) ; and we have shown that patients who lower their BMI are faster disease progression. In the second part, we studied the survival of SCA patients and developed a prognostic nomogram. We have shown that it is different according on the genotype. Survival is shorter in SCA1, intermediate in SCA2 and SCA3, and longer in SCA6. Finally, we assessed the long-term impact of ataxia progression on survival. We have shown that progression of ataxia is associated with shorter survival regardless of genotype. Only in SCA1 patients, we identified three subgroups of homogeneous patients in terms of disease progression and risk of death
Corneli, Marco. "Dynamic stochastic block models, clustering and segmentation in dynamic graphs". Thesis, Paris 1, 2017. http://www.theses.fr/2017PA01E012/document.
Texto completo da fonteThis thesis focuses on the statistical analysis of dynamic graphs, both defined in discrete or continuous time. We introduce a new extension of the stochastic block model (SBM) for dynamic graphs. The proposed approach, called dSBM, adopts non homogeneous Poisson processes to model the interaction times between pairs of nodes in dynamic graphs, either in discrete or continuous time. The intensity functions of the processes only depend on the node clusters, in a block modelling perspective. Moreover, all the intensity functions share some regularity properties on hidden time intervals that need to be estimated. A recent estimation algorithm for SBM, based on the greedy maximization of an exact criterion (exact ICL) is adopted for inference and model selection in dSBM. Moreover, an exact algorithm for change point detection in time series, the "pruned exact linear time" (PELT) method is extended to deal with dynamic graph data modelled via dSBM. The approach we propose can be used for change point analysis in graph data. Finally, a further extension of dSBM is developed to analyse dynamic net- works with textual edges (like social networks, for instance). In this context, the graph edges are associated with documents exchanged between the corresponding vertices. The textual content of the documents can provide additional information about the dynamic graph topological structure. The new model we propose is called "dynamic stochastic topic block model" (dSTBM).Graphs are mathematical structures very suitable to model interactions between objects or actors of interest. Several real networks such as communication networks, financial transaction networks, mobile telephone networks and social networks (Facebook, Linkedin, etc.) can be modelled via graphs. When observing a network, the time variable comes into play in two different ways: we can study the time dates at which the interactions occur and/or the interaction time spans. This thesis only focuses on the first time dimension and each interaction is assumed to be instantaneous, for simplicity. Hence, the network evolution is given by the interaction time dates only. In this framework, graphs can be used in two different ways to model networks. Discrete time […] Continuous time […]. In this thesis both these perspectives are adopted, alternatively. We consider new unsupervised methods to cluster the vertices of a graph into groups of homogeneous connection profiles. In this manuscript, the node groups are assumed to be time invariant to avoid possible identifiability issues. Moreover, the approaches that we propose aim to detect structural changes in the way the node clusters interact with each other. The building block of this thesis is the stochastic block model (SBM), a probabilistic approach initially used in social sciences. The standard SBM assumes that the nodes of a graph belong to hidden (disjoint) clusters and that the probability of observing an edge between two nodes only depends on their clusters. Since no further assumption is made on the connection probabilities, SBM is a very flexible model able to detect different network topologies (hubs, stars, communities, etc.)
Boucquemont, Julie. "Modèles statistiques pour l'étude de la progression de la maladie rénale chronique". Thesis, Bordeaux, 2014. http://www.theses.fr/2014BORD0411/document.
Texto completo da fonteThe objective of this thesis was to illustrate the benefit of using advanced statistical methods to study associations between risk factors and chrouic kidney disease (CKD) progression. In a first time, we conducted a literature review of statistical methods used to investigate risk factors of CKD progression, identified important methodological issues, and discussed solutions. In our sec ond work, we focused on survival analyses and issues with interval-censoring, which occurs when the event of interest is the progression to a specifie CKD stage, and competing risk with death. A comparison between standard survival models and the illness-death mode! for interval-censored data allowed us to illustrate the impact of modeling on the estimates of both the effects of risk factors and the probabilities of events, using data from the NephroTest cohort. Other works fo cused on analysis of longitudinal data on renal function. We illustrated the interest of linear mixed mode! in this context and presented its extension to account for sub-populations with different trajectories of renal function. We identified five classes, including one with a strong decline and one with an improvement of renal function over time. Severa! perspectives on predictions bind the two types of analyses presented in this thesis
Livros sobre o assunto "Modèle latent"
Stefanadis, Chris. Sunk costs, contestability, and the latent contract market. [New York, N.Y.]: Federal Reserve Bank of New York, 1999.
Encontre o texto completo da fonteBates, David S. Maximum likelihood estimation of latent affine processes. Cambridge, Mass: National Bureau of Economic Research, 2003.
Encontre o texto completo da fonteGaver, Donald Paul. Latent factor models and analyses for operator response times. Monterey, Calif: Naval Postgraduate School, 1990.
Encontre o texto completo da fonteMuthen, Linda K. Mplus: Statistical analysis with latent variables : user's guide. 4a ed. Los Angeles, CA: Muthén & Muthén, 2007.
Encontre o texto completo da fonteWaldegaray, Marta Inès. Réécritures en Amérique latine, les modèles décentrés. Metz: Université Paul Verlaine Metz, centre de recherches écritures, 2009.
Encontre o texto completo da fonteGoodman, Leo A. Analyzing qualitative/categorical data: Log-linear models and latent structure analysis. Lanham, MD: University Press of America, 1985.
Encontre o texto completo da fonteVermunt, Jeroen K. Log-linear event history analysis: A general approach with missing data, latent variables, and unobserved heterogeneity. Tilburg: Tilburg University Press, 1996.
Encontre o texto completo da fonteSparrow, Malcolm K. A topological approach to the matching of single fingerprints: Development of algorithms for use on latent fingermarks. Washington: National Bureau of Standards, 1985.
Encontre o texto completo da fonteSparrow, Malcolm K. A topological approach to the matching of single fingerprints: Development of algorithms for use on latent fingermarks. Gaithersburg, MD: U.S. Dept. of Commerce, National Bureau of Standards, 1985.
Encontre o texto completo da fonteSparrow, Malcolm K. A topological approach to the matching of single fingerprints: Development of algorithms for use on latent fingermarks. Gaithersburg, MD: U.S. Dept. of Commerce, National Bureau of Standards, 1985.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Modèle latent"
Flaherty, Brian P., e Cara J. Kiff. "Latent class and latent profile models." In APA handbook of research methods in psychology, Vol 3: Data analysis and research publication., 391–404. Washington: American Psychological Association, 2012. http://dx.doi.org/10.1037/13621-019.
Texto completo da fonteNewsom, Jason T. "Latent Class and Latent Transition Models". In Longitudinal Structural Equation Modeling, 308–38. 2a ed. New York: Routledge, 2023. http://dx.doi.org/10.4324/9781003263036-10.
Texto completo da fonteFlaherty, Brian P., Liying Wang e Cara J. Kiff. "Latent class and latent profile models." In APA handbook of research methods in psychology: Data analysis and research publication (Vol. 3) (2nd ed.)., 411–27. Washington: American Psychological Association, 2023. http://dx.doi.org/10.1037/0000320-018.
Texto completo da fonteMcGrath, Robert E. "Latent-variable models." In Quantitative models in psychology., 149–75. Washington: American Psychological Association, 2011. http://dx.doi.org/10.1037/12316-007.
Texto completo da fonteBishop, Christopher M. "Latent Variable Models". In Learning in Graphical Models, 371–403. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5014-9_13.
Texto completo da fonteZwiernik, Piotr. "Latent Tree Models". In Handbook of Graphical Models, 265–88. Boca Raton, Florida : CRC Press, c2019.: CRC Press, 2018. http://dx.doi.org/10.1201/9780429463976-11.
Texto completo da fonteBeaujean, A. Alexander, e Grant B. Morgan. "Latent Variable Models". In Human–Computer Interaction Series, 233–50. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-26633-6_10.
Texto completo da fonteClogg, Clifford C. "Latent Class Models". In Handbook of Statistical Modeling for the Social and Behavioral Sciences, 311–59. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4899-1292-3_6.
Texto completo da fonteKeith, Timothy Z. "Latent Growth Models". In Multiple Regression and Beyond, 513–33. Third Edition. | New York : Routledge, 2019. | Revised edition of the author’s Multiple regression and beyond, 2015.: Routledge, 2019. http://dx.doi.org/10.4324/9781315162348-21.
Texto completo da fonteHox, Joop J., Mirjam Moerbeek e Rens van de Schoot. "Latent Curve Models". In Multilevel Analysis, 294–304. Third edition. | New York, NY : Routledge, 2017. |: Routledge, 2017. http://dx.doi.org/10.4324/9781315650982-16.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Modèle latent"
Yu, Xuemin, Fahim Dalvi, Nadir Durrani, Marzia Nouri e Hassan Sajjad. "Latent Concept-based Explanation of NLP Models". In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 12435–59. Stroudsburg, PA, USA: Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.692.
Texto completo da fonteBlattmann, Andreas, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, Sanja Fidler e Karsten Kreis. "Align Your Latents: High-Resolution Video Synthesis with Latent Diffusion Models". In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2023. http://dx.doi.org/10.1109/cvpr52729.2023.02161.
Texto completo da fonteLu, Tianyi, Xing Zhang, Jiaxi Gu, Renjing Pei, Songcen Xu, Xingjun Ma, Hang Xu e Zuxuan Wu. "Fuse Your Latents: Video Editing with Multi-source Latent Diffusion Models". In MM '24: The 32nd ACM International Conference on Multimedia, 6745–54. New York, NY, USA: ACM, 2024. http://dx.doi.org/10.1145/3664647.3680683.
Texto completo da fonteShtoff, Alex, e Yair Koren. "Mitigating Divergence of Latent Factors via Dual Ascent for Low Latency Event Prediction Models". In 2021 IEEE International Conference on Big Data (Big Data). IEEE, 2021. http://dx.doi.org/10.1109/bigdata52589.2021.9671859.
Texto completo da fonteUrtasun, Raquel, David J. Fleet, Andreas Geiger, Jovan Popović, Trevor J. Darrell e Neil D. Lawrence. "Topologically-constrained latent variable models". In the 25th international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1390156.1390292.
Texto completo da fonteAgarwal, Deepak, e Bee-Chung Chen. "Regression-based latent factor models". In the 15th ACM SIGKDD international conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1557019.1557029.
Texto completo da fonteWillems, J. C., e J. W. Nieuwenhuis. "Continuity of latent variable models". In 29th IEEE Conference on Decision and Control. IEEE, 1990. http://dx.doi.org/10.1109/cdc.1990.203519.
Texto completo da fonteXu, Minjie, e Jun Zhu. "Discriminative infinite latent feature models". In 2013 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP). IEEE, 2013. http://dx.doi.org/10.1109/chinasip.2013.6625324.
Texto completo da fonteLiu, Yuhao, e Petar M. Djuric. "Tracking the Dimensions of Latent Spaces of Gaussian Process Latent Variable Models". In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022. http://dx.doi.org/10.1109/icassp43922.2022.9746538.
Texto completo da fonte"Initialization Framework for Latent Variable Models". In International Conference on Pattern Recognition Applications and Methods. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0004826302270232.
Texto completo da fonteRelatórios de organizações sobre o assunto "Modèle latent"
Liu, Songqi. Mixture Models: From Latent Classes/Profiles to Latent Growth, Transitions, and Multilevel Mixture Models. Instats Inc., 2022. http://dx.doi.org/10.61700/ky72m8g8cc8x2469.
Texto completo da fonteZhang, Zhen. Longitudinal SEM in Mplus: Latent Growth and Cross-Lagged Models. Instats Inc., 2022. http://dx.doi.org/10.61700/shmr7uf60jtgi469.
Texto completo da fonteZyphur, Michael. Longitudinal SEM in Mplus: Latent Growth and Cross-Lagged Panel Models. Instats Inc., 2022. http://dx.doi.org/10.61700/zvz8cn20pod2l469.
Texto completo da fonteZhang, Zhen. Longitudinal SEM in Mplus: Latent Growth and Cross-Lagged Panel Models. Instats Inc., 2022. http://dx.doi.org/10.61700/k7ip0jnkhqk0z469.
Texto completo da fonteZyphur, Michael. Longitudinal SEM in R: Latent Growth and Cross-Lagged Panel Models. Instats Inc., 2022. http://dx.doi.org/10.61700/0cgexcmkbt2w4469.
Texto completo da fonteRaykov, Tenko. Latent Class Analysis and Mixture Modeling. Instats Inc., 2023. http://dx.doi.org/10.61700/tkd5fah8evykd469.
Texto completo da fonteMislevy, Robert J., e Kathleen M. Sheehan. The Information Matrix in Latent-Variable Models. Fort Belvoir, VA: Defense Technical Information Center, abril de 1988. http://dx.doi.org/10.21236/ada196609.
Texto completo da fonteAnandkumar, Anima, Rong Ge, Daniel Hsu, Sham M. Kakade e Matus Telgarsky. Tensor Decompositions for Learning Latent Variable Models. Fort Belvoir, VA: Defense Technical Information Center, dezembro de 2012. http://dx.doi.org/10.21236/ada604494.
Texto completo da fonteGertler, Paul. A Latent Variable Model of Quality Determination. Cambridge, MA: National Bureau of Economic Research, outubro de 1985. http://dx.doi.org/10.3386/w1750.
Texto completo da fonteVickers, Jr, e Ross R. A Latent Trait Model of Simulated Combat Performance. Fort Belvoir, VA: Defense Technical Information Center, fevereiro de 2010. http://dx.doi.org/10.21236/ada562869.
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