Bibliografías temáticas / Latent

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Literatura académica sobre el tema "Latent"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 25 de julio de 2025

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Artículos de revistas sobre el tema "Latent"

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Keeling, R. "Latest developments in latent defects insurance." Property Management 11, no. 3 (1993): 220–25. http://dx.doi.org/10.1108/eum0000000003400.

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Avrahami, Omri, Ohad Fried, and Dani Lischinski. "Blended Latent Diffusion." ACM Transactions on Graphics 42, no. 4 (2023): 1–11. http://dx.doi.org/10.1145/3592450.

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The tremendous progress in neural image generation, coupled with the emergence of seemingly omnipotent vision-language models has finally enabled text-based interfaces for creating and editing images. Handling generic images requires a diverse underlying generative model, hence the latest works utilize diffusion models, which were shown to surpass GANs in terms of diversity. One major drawback of diffusion models, however, is their relatively slow inference time. In this paper, we present an accelerated solution to the task of local text-driven editing of generic images, where the desired edit
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Wolfson, Susan J. "Yeats's Latent Keats / Keats's Latent Yeats." PMLA/Publications of the Modern Language Association of America 131, no. 3 (2016): 603–21. http://dx.doi.org/10.1632/pmla.2016.131.3.603.

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Keats's tracks into the nineteenth century angle toward a “modernism” often defined at his expense—yet with latent identifications. In relations of past and present, figurai identifications may register in nuances different from conscious allusion or the psychodramas of influence, ravages and resistance, hauntings and felt belatedness that issue in self-interested misreadings. “Latent Keats” and “Latent Yeats” play into an important, underreported current in both Keats studies and Yeats studies: a “Long Romanticism” in intimate verbal figures that trouble any “Modernism” of definitional differ
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McCutcheon, Allen L., Rolf Langeheine, and Jurgen Rost. "Latent Trait and Latent Class Models." Contemporary Sociology 18, no. 5 (1989): 836. http://dx.doi.org/10.2307/2073408.

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Guo, J. "Latent class regression on latent factors." Biostatistics 7, no. 1 (2005): 145–63. http://dx.doi.org/10.1093/biostatistics/kxi046.

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Chaudhary, Neha, and Priti Dimri. "LATENT FINGERPRINT IMAGE ENHANCEMENT BASED ON OPTIMIZED BENT IDENTITY BASED CONVOLUTIONAL NEURAL NETWORK." Indian Journal of Computer Science and Engineering 12, no. 5 (2021): 1477–93. http://dx.doi.org/10.21817/indjcse/2021/v12i5/211205124.

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Fingerprints are unique biometric systems (BSs) in which none of the human possesses similar fingerprint structures. It is one of the most significant biometric processes used in the identification of criminals. Latent fingerprints or latents are generated mainly by the finger sweat or oil deposits which is left by the suspects unintentionally. The impressions of latents are blurred or smudgy in nature and not viewed by naked eye. These fingerprints are of low quality, corrupted by noise, degraded by technological factors and exhibit minor details. Latents display consistent structural info wh
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Stevens, Jesse, Daniel N. Wilke, and Isaac I. Setshedi. "Enhancing LS-PIE’s Optimal Latent Dimensional Identification: Latent Expansion and Latent Condensation." Mathematical and Computational Applications 29, no. 4 (2024): 65. http://dx.doi.org/10.3390/mca29040065.

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The Latent Space Perspicacity and Interpretation Enhancement (LS-PIE) framework enhances dimensionality reduction methods for linear latent variable models (LVMs). This paper extends LS-PIE by introducing an optimal latent discovery strategy to automate identifying optimal latent dimensions and projections based on user-defined metrics. The latent condensing (LCON) method clusters and condenses an extensive latent space into a compact form. A new approach, latent expansion (LEXP), incrementally increases latent dimensions using a linear LVM to find an optimal compact space. This study compares
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Zhang, Rongchao, Yu Huang, Yiwei Lou, et al. "Exploit Your Latents: Coarse-Grained Protein Backmapping with Latent Diffusion Models." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 1 (2025): 1111–19. https://doi.org/10.1609/aaai.v39i1.32098.

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Coarse-grained (CG) molecular dynamics of proteins is a preferred approach to studying large molecules on extended time scales by condensing the entire atomic model into a limited number of pseudo-atoms and preserving the thermodynamic properties of the system. However, the significantly increased efficiency impedes the analysis of substantial physicochemical information, since high-resolution atomic details are sacrificed to accelerate simulation. In this paper, we propose LatCPB, a generative approach based on diffusion that enables high-resolution backmapping of CG proteins. Specifically, o
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FLORES, RICARDO, SONIA DELGADO, MARÍA-ELENA RODIO, SILVIA AMBRÓS, CARMEN HERNÁNDEZ, and FRANCESCO DI SERIO. "Peach latent mosaic viroid: not so latent." Molecular Plant Pathology 7, no. 4 (2006): 209–21. http://dx.doi.org/10.1111/j.1364-3703.2006.00332.x.

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Croon, Marcel. "Latent class analysis with ordered latent classe." British Journal of Mathematical and Statistical Psychology 43, no. 2 (1990): 171–92. http://dx.doi.org/10.1111/j.2044-8317.1990.tb00934.x.

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Tesis sobre el tema "Latent"

1

Anaya, Leticia H. "Comparing Latent Dirichlet Allocation and Latent Semantic Analysis as Classifiers." Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc103284/.

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In the Information Age, a proliferation of unstructured text electronic documents exists. Processing these documents by humans is a daunting task as humans have limited cognitive abilities for processing large volumes of documents that can often be extremely lengthy. To address this problem, text data computer algorithms are being developed. Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are two text data computer algorithms that have received much attention individually in the text data literature for topic extraction studies but not for document classification nor for
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Xiong, Hao. "Diversified Latent Variable Models." Thesis, The University of Sydney, 2018. http://hdl.handle.net/2123/18512.

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Latent variable model is a common probabilistic framework which aims to estimate the hidden states of observations. More specifically, the hidden states can be the position of a robot, the low dimensional representation of an observation. Meanwhile, various latent variable models have been explored, such as hidden Markov models (HMM), Gaussian mixture model (GMM), Bayesian Gaussian process latent variable model (BGPLVM), etc. Moreover, these latent variable models have been successfully applied to a wide range of fields, such as robotic navigation, image and video compression, natural language
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Etessami, Pantea. "Mutagenesis studies on the genome of cassava latent virus : (African cassava latent virus)." Thesis, University of East Anglia, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.235620.

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Murphy, Sean Michael. "Disease management and latent choices." Online access for everyone, 2008. http://www.dissertations.wsu.edu/Dissertations/Summer2008/S_Murphy_062608.pdf.

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Cartmill, Ian. "Builders' liability for latent defects." Thesis, University of Oxford, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302694.

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Shafia, Aminath. "Latent infection of Botrytis cinerea." Thesis, University of Reading, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.499372.

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Latent B. cinerea was detected in nine symptomless wild host species from the families Asteraceae and Brassicaceae, in addition to greenhouse grown lettuce. Conventional testing methods revealed that latent B. cinerea was equally prevalent in the root system as the above ground parts. Incidence of latent infection was moderate in some species (Achillea milleforlium, Arabidopsis thaliana, Centraurea nigra, Cirsium vulgare, Senecio jacobaea, Senecio vulgaris and Taraaxacum agg.) and rare in others (Tussilago farfara and Bellis perennis). In greenhouse lettuce, latent infection was activated by p
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Ponweiser, Martin. "Latent Dirichlet Allocation in R." WU Vienna University of Economics and Business, 2012. http://epub.wu.ac.at/3558/1/main.pdf.

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Topic models are a new research field within the computer sciences information retrieval and text mining. They are generative probabilistic models of text corpora inferred by machine learning and they can be used for retrieval and text mining tasks. The most prominent topic model is latent Dirichlet allocation (LDA), which was introduced in 2003 by Blei et al. and has since then sparked off the development of other topic models for domain-specific purposes. This thesis focuses on LDA's practical application. Its main goal is the replication of the data analyses from the 2004 LDA paper ``Findi
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Creagh-Osborne, Jane. "Latent variable generalized linear models." Thesis, University of Plymouth, 1998. http://hdl.handle.net/10026.1/1885.

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Generalized Linear Models (GLMs) (McCullagh and Nelder, 1989) provide a unified framework for fixed effect models where response data arise from exponential family distributions. Much recent research has attempted to extend the framework to include random effects in the linear predictors. Different methodologies have been employed to solve different motivating problems, for example Generalized Linear Mixed Models (Clayton, 1994) and Multilevel Models (Goldstein, 1995). A thorough review and classification of this and related material is presented. In Item Response Theory (IRT) subjects are tes
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Mao, Cheng Ph D. Massachusetts Institute of Technology. "Matrix estimation with latent permutations." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117863.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mathematics, 2018.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 151-167).<br>Motivated by various applications such as seriation, network alignment and ranking from pairwise comparisons, we study the problem of estimating a structured matrix with rows and columns shuffled by latent permutations, given noisy and incomplete observations of its entries. This problem is at the intersection of shape constrained estimation which has a long history in statistics, and latent permutation learn
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Dallaire, Patrick. "Bayesian nonparametric latent variable models." Doctoral thesis, Université Laval, 2016. http://hdl.handle.net/20.500.11794/26848.

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L’un des problèmes importants en apprentissage automatique est de déterminer la complexité du modèle à apprendre. Une trop grande complexité mène au surapprentissage, ce qui correspond à trouver des structures qui n’existent pas réellement dans les données, tandis qu’une trop faible complexité mène au sous-apprentissage, c’est-à-dire que l’expressivité du modèle est insuffisante pour capturer l’ensemble des structures présentes dans les données. Pour certains modèles probabilistes, la complexité du modèle se traduit par l’introduction d’une ou plusieurs variables cachées dont le rôle est d’exp
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Libros sobre el tema "Latent"

1

Langeheine, Rolf, and Jürgen Rost, eds. Latent Trait and Latent Class Models. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4757-5644-9.

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Rolf, Langeheine, Rost Jürgen, and Universität Kiel. Institut für die Pädagogik der Naturwissenschaften., eds. Latent trait and latent class models. Plenum Press, 1988.

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Collins, Linda M. Latent class and latent transition analysis. Wiley, 2010.

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A, Marcoulides George, and Moustaki Irini, eds. Latent variable and latent structure models. Lawrence Earlbaum Publishers, 2002.

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Lubow, R. E., and Ina Weiner, eds. Latent Inhibition. Cambridge University Press, 2009. http://dx.doi.org/10.1017/cbo9780511730184.

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Forrellad, Luisa. Foc latent. Angle Editorial, 2006.

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Barbu, Ion. Nadir latent. Minerva, 1985.

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8

Royal Institute of British Architects., ed. Latent defects. RIBA, 1990.

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Ghasi, Samuel. Latent error. Rhyce Kerex Publishers, 2016.

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Frühwirth, Michaela. Latent image. Roma Publications, 2016.

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Capítulos de libros sobre el tema "Latent"

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Herwig, Heinz. "Latente Wärme (latent heat)." In Wärmeübertragung A-Z. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-56940-1_32.

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Flaherty, Brian P., Liying Wang, and 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.). American Psychological Association, 2023. http://dx.doi.org/10.1037/0000320-018.

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Newsom, Jason T. "Latent Class and Latent Transition Models." In Longitudinal Structural Equation Modeling, 2nd ed. Routledge, 2023. http://dx.doi.org/10.4324/9781003263036-10.

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Flaherty, Brian P., and Cara J. Kiff. "Latent class and latent profile models." In APA handbook of research methods in psychology, Vol 3: Data analysis and research publication. American Psychological Association, 2012. http://dx.doi.org/10.1037/13621-019.

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Hofmans, Joeri. "Latent Class and Latent Profile Analysis." In Workforce Analytics. Routledge, 2025. https://doi.org/10.4324/9781003190097-8.

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Miller, Laura T., Lionel Stange, Charles MacVean, et al. "Latent Infection." In Encyclopedia of Entomology. Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6359-6_1969.

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Miller, Laura T., Lionel Stange, Charles MacVean, et al. "Latent Learning." In Encyclopedia of Entomology. Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6359-6_1970.

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Fernandes, Rodney A. "Latent Functionality." In Protecting-Group-Free Organic Synthesis. John Wiley & Sons, Ltd, 2018. http://dx.doi.org/10.1002/9781119295266.ch9.

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Fischer, Gabriele, Annemarie Unger, W. Wolfgang Fleischhacker, et al. "Latent Inhibition." In Encyclopedia of Psychopharmacology. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-68706-1_344.

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Pierrehumbert, Ray. "Latent Heat." In Encyclopedia of Astrobiology. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-11274-4_130.

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Actas de conferencias sobre el tema "Latent"

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Wu, Zilong, Hideki Murata, Nayu Takahashi, Qiyu Wu, and Yoshimasa Tsuruoka. "LatentPS: Image Editing Using Latent Representations in Diffusion Models." In 2025 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW). IEEE, 2025. https://doi.org/10.1109/wacvw65960.2025.00023.

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Jin, Yawei, Yang Zhang, Hong Zhang, et al. "On Latent Defect Acceleration." In 2024 2nd International Symposium of Electronics Design Automation (ISEDA). IEEE, 2024. http://dx.doi.org/10.1109/iseda62518.2024.10617882.

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Xie, Zhouhang, Tushar Khot, Bhavana Dalvi Mishra, et al. "Latent Factor Models Meets Instructions: Goal-conditioned Latent Factor Discovery without Task Supervision." In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). Association for Computational Linguistics, 2025. https://doi.org/10.18653/v1/2025.naacl-long.554.

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Komar, Alexander, Michael Kammerer, Saeedeh Barzegar Khalilsaraei, and Ursula Augsdörfer. "LatEd: A Geometric Latent Vector Editor." In Computer Science Research Notes. University of West Bohemia, Czech Republic, 2024. http://dx.doi.org/10.24132/csrn.3401.35.

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Using a neural network approach, a shape may be compressed to a one-dimensional vector, the so-called latent dimension or latent vector. This latent shape dimension is examined in this paper. This latent vector of a shape is used to identify the corresponding shape in a database. Two types of networks are evaluated in terms of lookup accuracy and reconstruction quality using a database of Lego pieces. Even with small training set a reasonable robustness to rotation and translation of the shapes was achieved. While a human can interpret uncompressed data just fine, the compressed values of the
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Sankaran, Anush, Tejas I. Dhamecha, Mayank Vatsa, and Richa Singh. "On matching latent to latent fingerprints." In 2011 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2011. http://dx.doi.org/10.1109/ijcb.2011.6117525.

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"Latent Ambiguity in Latent Semantic Analysis?" In International Conference on Pattern Recognition Applications and Methods. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004178301150120.

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Nakjai, Pisit, Jiradej Ponsawat, and Tatpong Katanyukul. "Latent cognizance." In the 2nd International Conference. ACM Press, 2019. http://dx.doi.org/10.1145/3357254.3357266.

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Korman, Simon, and Roee Litman. "Latent RANSAC." In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2018. http://dx.doi.org/10.1109/cvpr.2018.00700.

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Agarwal, Deepak, and Bee-Chung Chen. "Latent OLAP." In the 2011 international conference. ACM Press, 2011. http://dx.doi.org/10.1145/1989323.1989415.

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Beutel, Alex, Paul Covington, Sagar Jain, et al. "Latent Cross." In WSDM 2018: The Eleventh ACM International Conference on Web Search and Data Mining. ACM, 2018. http://dx.doi.org/10.1145/3159652.3159727.

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Informes sobre el tema "Latent"

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Henn, Soeren, and James Robinson. Africa's Latent Assets. National Bureau of Economic Research, 2021. http://dx.doi.org/10.3386/w28603.

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Grinfeld, Michael A., and Steven B. Segletes. Latent Work and Latent Heat of the Liquid/Vapor Transformation. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada608749.

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Taylor, Melissa, Will Chapman, Austin Hicklin, et al. Latent Interoperability Transmission Specification. National Institute of Standards and Technology, 2013. http://dx.doi.org/10.6028/nist.sp.1152.

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Chierichetti, Maria, and Fatemeh Davoudi Kakhki. Latent Active Transportation Methodology. Mineta Transportation Institute, 2025. https://doi.org/10.31979/mti.2025.2309.

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Understanding and estimating latent demand for active transportation, such as walking and cycling, is essential for designing infrastructure and policies that promote sustainable mobility. Unlike traditional demand models that focus on observed trips, latent demand estimation seeks to quantify the unrealized potential for active travel due to barriers such as inadequate infrastructure, safety concerns, or lack of connectivity. This study develops a comprehensive latent demand model tailored for California, integrating geospatial analysis and multimodal accessibility assessments. The methodolog
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Garris, Michael D. Latent fingerprint training with NIST special database 27 and universal latent workstation. National Institute of Standards and Technology, 2001. http://dx.doi.org/10.6028/nist.ir.6799.

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Massague, Joan. Dissecting and Targeting Latent Metastasis. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada605186.

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Lee, Paul, Haiying Guan, Andrew Dienstfrey, Mary Theofanos, Brian Stanton, and Matthew T. Schwarz. Forensic latent fingerprint preprocessing assessment. National Institute of Standards and Technology, 2018. http://dx.doi.org/10.6028/nist.ir.8215.

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Lettau, Martin, and Markus Pelger. Estimating Latent Asset-Pricing Factors. National Bureau of Economic Research, 2018. http://dx.doi.org/10.3386/w24618.

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Bonhomme, Stéphane, and Manuel Arellano. Recovering Latent Variables by Matching. The IFS, 2020. http://dx.doi.org/10.1920/wp.cem.2020.220.

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Honkala, Alexander. Latent Space Journal Mission Statement. ResearchHub Technologies, Inc., 2024. http://dx.doi.org/10.55277/researchhub.sokdroqu.

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