Relevant bibliographies by topics / Tabular data

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Tabular data'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Tabular data"

1

Altman, Naomi, and Martin Krzywinski. "Tabular data." Nature Methods 14, no. 4 (2017): 329–30. http://dx.doi.org/10.1038/nmeth.4239.

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Eken, Süleyman, Ahmet Sayar, and Kürşat Topçuoğlu. "AutoTest: Automation to Test Tabular Data Quality." International Journal of Computer and Electrical Engineering 6, no. 4 (2014): 365–68. http://dx.doi.org/10.7763/ijcee.2014.v6.854.

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Altman, Naomi, and Martin Krzywinski. "Author Correction: Tabular data." Nature Methods 16, no. 7 (2019): 658. http://dx.doi.org/10.1038/s41592-019-0474-z.

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Badaro, Gilbert, and Paolo Papotti. "Transformers for tabular data representation." Proceedings of the VLDB Endowment 15, no. 12 (2022): 3746–49. http://dx.doi.org/10.14778/3554821.3554890.

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In the last few years, the natural language processing community witnessed advances in neural representations of free texts with transformer-based language models (LMs). Given the importance of knowledge available in relational tables, recent research efforts extend LMs by developing neural representations for tabular data. In this tutorial, we present these proposals with two main goals. First, we introduce to a database audience the potentials and the limitations of current models. Second, we demonstrate the large variety of data applications that benefit from the transformer architecture. T
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Kelly, James P., Bruce L. Golden, Arjang A. Assad, and Edward K. Baker. "Controlled Rounding of Tabular Data." Operations Research 38, no. 5 (1990): 760–72. http://dx.doi.org/10.1287/opre.38.5.760.

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Menon, Anil, and Nadhamuni Nerella. "Communicating Tabular Data Using ORACLE." Pharmaceutical Development and Technology 5, no. 3 (2000): 423–31. http://dx.doi.org/10.1081/pdt-100100559.

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Humpal, John J. "Numbers, Statistics, and Tabular Data." Radiology 218, no. 1 (2001): 12. http://dx.doi.org/10.1148/radiology.218.1.r01ja6812.

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MORRISON, PHILIP S. "Symbolic Representation of Tabular Data." New Zealand Journal of Geography 79, no. 1 (2008): 11–18. http://dx.doi.org/10.1111/j.0028-8292.1985.tb00199.x.

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Gonzalez, Joe Fred, and Lawrence H. Cox. "Software for tabular data protection." Statistics in Medicine 24, no. 4 (2005): 659–69. http://dx.doi.org/10.1002/sim.2043.

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Zhou, Zhi, Kun-Yang Yu, Lan-Zhe Guo, and Yu-Feng Li. "Fully Test-time Adaptation for Tabular Data." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 21 (2025): 23027–35. https://doi.org/10.1609/aaai.v39i21.34466.

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Tabular data plays a vital role in various real-world scenarios and finds extensive applications. Although recent deep tabular models have shown remarkable success, they still struggle to handle data distribution shifts, leading to performance degradation when testing distributions change. To remedy this, a robust tabular model must adapt to generalize to unknown distributions during testing. In this paper, we investigate the problem of fully test-time adaptation (FTTA) for tabular data, where the model is adapted using only the testing data. We identify three key challenges: the existence of
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Dissertations / Theses on the topic "Tabular data"

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Xu, Lei S. M. Massachusetts Institute of Technology. "Synthesizing tabular data using conditional GAN." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/128349.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2020<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 89-93).<br>In data science, the ability to model the distribution of rows in tabular data and generate realistic synthetic data enables various important applications including data compression, data disclosure, and privacy-preserving machine learning. However, because tabular data usually contains a mix of discrete and continuous columns, building such a model is a non-trivial task.
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Liu, Zhicheng. "Network-based visual analysis of tabular data." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43687.

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Tabular data is pervasive in the form of spreadsheets and relational databases. Although tables often describe multivariate data without explicit network semantics, it may be advantageous to explore the data modeled as a graph or network for analysis. Even when a given table design conveys some static network semantics, analysts may want to look at multiple networks from different perspectives, at different levels of abstraction, and with different edge semantics. This dissertation is motivated by the observation that a general approach for performing multi-dimensional and multi-level network
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Caspár, Sophia. "Visualization of tabular data on mobile devices." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-68036.

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This thesis evaluates various ways of displaying tabular data on mobile devices using different responsive table solutions. It also presents a tool to help web developers and designers in the process of choosing and implementing a suitable table approach. The proposed solution for this thesis is a web system called The Visualizing Wizard that allows the user to answer some questions about the intended table and then get a recommended responsive table solution generated based on the answers. The system uses a rule-based approach via Prolog to match the answers to a set of rules and provide an a
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Braunschweig, Katrin. "Recovering the Semantics of Tabular Web Data." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-184502.

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The Web provides a platform for people to share their data, leading to an abundance of accessible information. In recent years, significant research effort has been directed especially at tables on the Web, which form a rich resource for factual and relational data. Applications such as fact search and knowledge base construction benefit from this data, as it is often less ambiguous than unstructured text. However, many traditional information extraction and retrieval techniques are not well suited for Web tables, as they generally do not consider the role of the table structure in reflecting
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Cappuzzo, Riccardo. "Deep learning models for tabular data curation." Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS047.

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La conservation des données est un sujet omniprésent et de grande envergure, qui touche tous les domaines, du monde universitaire à l'industrie. Les solutions actuelles reposent sur le travail manuel des utilisateurs du domaine, mais elles ne sont pas adaptées. Nous étudions comment appliquer l'apprentissage profond à la conservation des données tabulaires. Nous concentrons notre travail sur le développement de systèmes de curation de données non supervisés et sur la conception de systèmes de curation qui modélisent intrinsèquement les valeurs catégorielles dans leur forme brute. Nous implémen
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Baxter, Jay. "BayesDB : querying the probable implications of tabular data." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91451.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.<br>43<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 93-95).<br>BayesDB, a Bayesian database table, lets users query the probable implications of their tabular data as easily as an SQL database lets them query the data itself. Using the built-in Bayesian Query Language (BQL), users with little statistics knowledge can solve basic data science problems, such as detecting predictive relationships between variables, inferring missing valu
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Jiang, Ji Chu. "High Precision Deep Learning-Based Tabular Data Extraction." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/41699.

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The advancements of AI methodologies and computing power enables automation and propels the Industry 4.0 phenomenon. Information and data are digitized more than ever, millions of documents are being processed every day, they are fueled by the growth in institutions, organizations, and their supply chains. Processing documents is a time consuming laborious task. Therefore automating data processing is a highly important task for optimizing supply chains efficiency across all industries. Document analysis for data extraction is an impactful field, this thesis aims to achieve the vital steps in
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Rahman, Md Anisur. "Tabular Representation of Schema Mappings: Semantics and Algorithms." Thèse, Université d'Ottawa / University of Ottawa, 2011. http://hdl.handle.net/10393/20032.

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Our thesis investigates a mechanism for representing schema mapping by tabular forms and checking utility of the new representation. Schema mapping is a high-level specification that describes the relationship between two database schemas. Schema mappings constitute essential building blocks of data integration, data exchange and peer-to-peer data sharing systems. Global-and-local-as-view (GLAV) is one of the approaches for specifying the schema mappings. Tableaux are used for expressing queries and functional dependencies on a single database in a tabular form. In our thesis, we first introdu
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Baena, Mirabete Daniel. "Exact and heuristic methods for statistical tabular data protection." Doctoral thesis, Universitat Politècnica de Catalunya, 2017. http://hdl.handle.net/10803/456809.

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One of the main purposes of National Statistical Agencies (NSAs) is to provide citizens or researchers with a large amount of trustful and high quality statistical information. NSAs must guarantee that no confidential individual information can be obtained from the released statistical outputs. The discipline of Statistical disclosure control (SDC) aims to avoid that confidential information is derived from data released while, at the same time, maintaining as much as possible the data utility. NSAs work with two types of data: microdata and tabular data. Microdata files contain records of ind
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Karlsson, Anton, and Torbjörn Sjöberg. "Synthesis of Tabular Financial Data using Generative Adversarial Networks." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273633.

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Digitalization has led to tons of available customer data and possibilities for data-driven innovation. However, the data needs to be handled carefully to protect the privacy of the customers. Generative Adversarial Networks (GANs) are a promising recent development in generative modeling. They can be used to create synthetic data which facilitate analysis while ensuring that customer privacy is maintained. Prior research on GANs has shown impressive results on image data. In this thesis, we investigate the viability of using GANs within the financial industry. We investigate two state-of-the-
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Books on the topic "Tabular data"

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Ye, Andre, and Zian Wang. Modern Deep Learning for Tabular Data. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-8692-0.

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Gilbert, G. Nigel. Analyzing tabular data: Loglinear and logistic models for social researchers. UCL Press, 1993.

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United States. Bureau of Mines., ed. MULSIM/PC: A personal-computer-based structural analysis program for mine design in deep tabular deposits. U.S. Dept. of the Interior, Bureau of Mines, 1992.

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United States. Bureau of Mines., ed. MULSIM/PC: A personal-computer-based structural analysis program for mine design in deep tabular deposits. U.S. Dept. of the Interior, Bureau of Mines, 1992.

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Donato, D. A. MULSIM/PC: A personal computer-based structural analysis program for mine design in deep tabular deposits. U.S. Dept. of the Interior, Bureau of Mines, 1992.

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Spamer, Earle E. Geology of the Grand Canyon: A guide and index to published graphic and tabular data (excluding paleontology). Geological Society of America, 1990.

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B, Taylor Richard. GS MRDS: A system based on the data fields used in the national MRDS system but using dBASE III and a microcomputer (IBM PC) or compatible) for organizing data on mineral resource occurrences and providing tabular and graphic output. U.S. Dept. of the Interior, Geological Survey, 1986.

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B, Taylor Richard. GS MRDS: A system based on the data fields used in the national MRDS system but using dBASE III and a microcomputer (IBM PC) or compatible) for organizing data on mineral resource occurrences and providing tabular and graphic output. U.S. Dept. of the Interior, Geological Survey, 1986.

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I, Selner G., Johnson Bruce R, and Geological Survey (U.S.), eds. GS MRDS: A system based on the data fields used in the national MRDS system but using dBASE III and a microcomputer (IBM PC) or compatible) for organizing data on mineral resource occurrences and providing tabular and graphic output. U.S. Dept. of the Interior, Geological Survey, 1986.

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Haworth, Lauren E. PROC TABULATE by example. SAS Institute, 1999.

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Book chapters on the topic "Tabular data"

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Stowell, Sarah. "Tabular Data." In Using R for Statistics. Apress, 2014. http://dx.doi.org/10.1007/978-1-4842-0139-8_6.

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Domingo-Ferrer, Josep. "Tabular Data." In Encyclopedia of Database Systems. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4899-7993-3_1493-2.

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Willenborg, Leon, and Ton de Waal. "Tabular Data." In Statistical Disclosure Control in Practice. Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4612-4028-0_6.

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Dalgaard, Peter. "Tabular data." In Statistics and Computing. Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-79054-1_8.

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Domingo-Ferrer, Josep. "Tabular Data." In Encyclopedia of Database Systems. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_1493.

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Keydana, Sigrid. "Tabular Data." In Deep Learning and Scientific Computing with R torch. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003275923-20.

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Darrin, Speegle, and Clair Bryan. "Tabular Data." In Probability, Statistics, and Data. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003004899-10.

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Domingo-Ferrer, Josep. "Tabular Data." In Encyclopedia of Database Systems. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_1493.

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Gilbert, Nigel. "Modelling mobility and change." In Analyzing Tabular Data. Routledge, 2022. http://dx.doi.org/10.4324/9781003259701-7.

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Gilbert, Nigel. "Choosing and fitting models." In Analyzing Tabular Data. Routledge, 2022. http://dx.doi.org/10.4324/9781003259701-6.

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Conference papers on the topic "Tabular data"

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Tran, Quan M., Suong N. Hoang, Lam M. Nguyen, Dzung Phan, and Hoang Thanh Lam. "TabularFM: An Open Framework For Tabular Foundational Models." In 2024 IEEE International Conference on Big Data (BigData). IEEE, 2024. https://doi.org/10.1109/bigdata62323.2024.10826064.

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Mehra, Pavitra, and El Kindi Rezig. "Leveraging Structured and Unstructured Data for Tabular Data Cleaning." In 2024 IEEE International Conference on Big Data (BigData). IEEE, 2024. https://doi.org/10.1109/bigdata62323.2024.10825257.

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Johnson, Matthew, Sabbir M. Rashid, and Deborah L. McGuinness. "Improving Tabular Reusability Through Data Dictionary Descriptions." In 2025 19th International Conference on Semantic Computing (ICSC). IEEE, 2025. https://doi.org/10.1109/icsc64641.2025.00035.

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Nguyen, Dang, Sunil Gupta, Kien Do, Thin Nguyen, and Svetha Venkatesh. "Generating Realistic Tabular Data with Large Language Models." In 2024 IEEE International Conference on Data Mining (ICDM). IEEE, 2024. https://doi.org/10.1109/icdm59182.2024.00040.

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Madhusudhanan, Kiran, Gunnar Behrens, Maximilian Stubbemann, and Lars Schmidt-Thieme. "ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing." In 2024 IEEE International Conference on Big Data (BigData). IEEE, 2024. https://doi.org/10.1109/bigdata62323.2024.10825740.

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Lu, Jianbin, Shuai Han, Weidong Chen, and Leping Sun. "Denoising Diffusion Probabilistic Imputation Model for Tabular Data." In 2024 IEEE First International Conference on Data Intelligence and Innovative Application (DIIA). IEEE, 2024. https://doi.org/10.1109/diia62678.2024.10871307.

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Huang, Lu, and Anjie Peng. "Tabular Data Classification via an Improved Gated Transformer." In 2024 17th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI). IEEE, 2024. https://doi.org/10.1109/cisp-bmei64163.2024.10906087.

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Zhao, Zilong, Han Wu, Aad van Moorsel, and Lydia Y. Chen. "GTV: Generating Tabular Data via Vertical Federated Learning." In 2025 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE, 2025. https://doi.org/10.1109/dsn64029.2025.00019.

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Mathur, Arpit, and Kartik Shah. "TSDCG: Tabular Synthetic Data with Code Generation LLMs." In 2025 3rd International Conference on Inventive Computing and Informatics (ICICI). IEEE, 2025. https://doi.org/10.1109/icici65870.2025.11069449.

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Zhou, Yunfan, Ying Li, Xuxue Sun, Zhong Wang, Dongquan Li, and Pengfei Shan. "Tabular Feature Guided Multimodal Cardiovascular Disease Classification." In 2025 10th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA). IEEE, 2025. https://doi.org/10.1109/icccbda64898.2025.11030487.

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Reports on the topic "Tabular data"

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Garton, Timothy. Data enrichment and enhanced accessibility of waterborne commerce numerical data : spatially depicting the National Waterway Network. Engineer Research and Development Center (U.S.), 2020. http://dx.doi.org/10.21079/11681/39223.

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This report provides methodologies and processes of data enrichment and enhanced accessibility of Waterborne Commerce and Statistics Center (WCSC) maintained databases. These databases house tabular and statistical data that reports on The U.S. Army Corps of Engineers (USACE) Civil Works Division National Waterway Network (NWN), which geospatially represents approximately 1,000 harbors and 25,000 miles of channels and waterways. WCSC is a division of The Institute for Water Resources (IWR). They have been tasked with the international collection, maintenance, and archival of all records involv
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Christensen, Noah, Austin Jensen, and Stephanie Mills. Intrusive Basemap of Utah. Utah Geological Survey, 2025. https://doi.org/10.34191/ds-2.

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The Intrusive Basemap of Utah is a geodatabase and tabular dataset of mapping, geochemical, and geochronological data from known, surface-exposed igneous intrusive rocks across Utah. The purpose of this database is to provide a central source of data relevant to the study and interpretation of magmatic activity throughout Utah’s geologic history.
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Hazen, T. C. Operations Support of Phase 2 Integrated Demonstration In Situ Bioremediation. Volume 2, Final report: Data in tabular form, Disks 2,3,4. Office of Scientific and Technical Information (OSTI), 1993. http://dx.doi.org/10.2172/10161904.

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Hazen, T. C. Operations Support of Phase 2 Integrated Demonstration In Situ Bioremediation. Volume 3, Final report: Data in graphical form, Disks 1,2,3,4; Averaged data in tabular form, Disks 1,2. Office of Scientific and Technical Information (OSTI), 1993. http://dx.doi.org/10.2172/10161897.

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Hazen, T. C. Operations Support of Phase 2 Integrated Demonstration In Situ Bioremediation. Volume 4, Final report: Averaged data in tabular form, Disks 3,4; Averaged data in graphical form, Disks 1,2,3,4. Office of Scientific and Technical Information (OSTI), 1993. http://dx.doi.org/10.2172/10161901.

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Hazen, T. C. Operations Support of Phase 2 Integrated Demonstration In Situ Bioremediation. Volume 1, Final report: Final report text data in tabular form, Disk 1. Office of Scientific and Technical Information (OSTI), 1993. http://dx.doi.org/10.2172/10161907.

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Leis, Flamberg, and Rose. BB78ES8 Vintage Line Pipe Properties via Battelle's Archives. Pipeline Research Council International, Inc. (PRCI), 2008. http://dx.doi.org/10.55274/r0011082.

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Pipeline fitness-for-service and maintenance prioritization both require knowledge of the line pipe�s mechanical properties and fracture resistance. This report presents such information for a broad range of steels, including vintage Grades A and B as well as early X-grades up through X52 produced from 1930 to 1970. Thirty-six data sets for steels over this range of grades were presented in terms of full-range curves for steels produced up through 1960, while results for another ~150 steels produced until 1970 were summarized in tabular format. Strength and toughness (via CVN and/or DWTT) data
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Kokurina, O., and A. Burov. Analytical report on the results of an empirical study of the characteristics and level of sociopolitical stability of student youth as a factor of sustainable development of the Russian statehood in the context of current global challenges. SIB-Expertise, 2022. http://dx.doi.org/10.12731/er0623.06122022.

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The Аnalytical report summarizes and interprets the results of empirical research of characteristics and level of sociopolitical stability of student youth as a factor of sustainable development of Russian statehood in the context of contemporary global challenges. The research is performed in the form of a sociological survey. Also in the specified result of intellectual activity the data on the revealed most significant channels, forms and directions of influence of the state youth and state national policy of the Russian Federation on sociopolitical stability are listed. The Аnalytical repo
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Casper, Gary, Stefanie Nadeau, and Thomas Parr. Acoustic amphibian monitoring, 2019 data summary: Isle Royale National Park. National Park Service, 2022. http://dx.doi.org/10.36967/2295506.

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Amphibians are a Vital Sign indicator for monitoring long-term ecosystem health in seven national park units that comprise the Great Lakes Network. We present here the results for 2019 amphibian monitoring at Isle Royale National Park (ISRO). Appendices contain tabular summaries for six years of cumulative results. The National Park Service Great Lakes Inventory and Monitoring Network established 10 permanent acoustic amphibian monitoring sites at ISRO in 2015. Acoustic samples are collected by placing automated recorders with omnidirectional stereo microphones at each of the 10 sampling sites
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Casper, Gary, Stefanie Nadeau, and Thomas Parr. Acoustic amphibian monitoring, 2019 data summary: Sleeping Bear Dunes National Lakeshore. National Park Service, 2022. http://dx.doi.org/10.36967/2295512.

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Amphibians are a Vital Sign indicator for monitoring long-term ecosystem health in seven national park units that comprise the Great Lakes Network. We present here the results for 2019 amphibian monitoring at Sleeping Bear Dunes National Lakeshore (SLBE). Appendices contain tabular summaries for six years of cumulative results. The National Park Service Great Lakes Inventory and Monitoring Network established 10 permanent acoustic amphibian monitoring sites at SLBE in 2013. Acoustic samples are collected by placing automated recorders with omnidirectional stereo microphones at each of the 10 s
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