Academic literature on the topic 'Broad Structural Representation Learning'
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Journal articles on the topic "Broad Structural Representation Learning"
Worden, Keith, and Graeme Manson. "The application of machine learning to structural health monitoring." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 365, no. 1851 (December 12, 2006): 515–37. http://dx.doi.org/10.1098/rsta.2006.1938.
Full textArney, Noah D., and Hilary P. Krygsman. "Work-Integrated Learning Policy in Alberta: A Post-Structural Analysis." Canadian Journal of Educational Administration and Policy, no. 198 (February 17, 2022): 97–110. http://dx.doi.org/10.7202/1086429ar.
Full textQuintana, Rafael. "The ecology of human behavior: A network perspective." Methodological Innovations 15, no. 1 (March 2022): 42–61. http://dx.doi.org/10.1177/20597991221077911.
Full textBingman, Verner P., and Rubén N. Muzio. "Reflections on the Structural-Functional Evolution of the Hippocampus: What Is the Big Deal about a Dentate Gyrus." Brain, Behavior and Evolution 90, no. 1 (2017): 53–61. http://dx.doi.org/10.1159/000475592.
Full textSingh, Ajay, Harman Preet Singh, Fakhre Alam, and Vikas Agrawal. "Role of Education, Training, and E-Learning in Sustainable Employment Generation and Social Empowerment in Saudi Arabia." Sustainability 14, no. 14 (July 19, 2022): 8822. http://dx.doi.org/10.3390/su14148822.
Full textMcConaghy, Cathryn. "on Pedagogy, Trauma and Difficult Memory: Remembering Namatjira, our Beloved." Australian Journal of Indigenous Education 32 (2003): 11–20. http://dx.doi.org/10.1017/s1326011100003781.
Full textOrynbaikyzy, Aiym, Ursula Gessner, Benjamin Mack, and Christopher Conrad. "Crop Type Classification Using Fusion of Sentinel-1 and Sentinel-2 Data: Assessing the Impact of Feature Selection, Optical Data Availability, and Parcel Sizes on the Accuracies." Remote Sensing 12, no. 17 (August 27, 2020): 2779. http://dx.doi.org/10.3390/rs12172779.
Full textFasoulis, Romanos, Georgios Paliouras, and Lydia E. Kavraki. "Graph representation learning for structural proteomics." Emerging Topics in Life Sciences 5, no. 6 (October 19, 2021): 789–802. http://dx.doi.org/10.1042/etls20210225.
Full textLi, Cheng-Te, and Hong-Yu Lin. "Structural Hierarchy-Enhanced Network Representation Learning." Applied Sciences 10, no. 20 (October 16, 2020): 7214. http://dx.doi.org/10.3390/app10207214.
Full textRomero, Lisa S. "Trust, behavior, and high school outcomes." Journal of Educational Administration 53, no. 2 (April 13, 2015): 215–36. http://dx.doi.org/10.1108/jea-07-2013-0079.
Full textDissertations / Theses on the topic "Broad Structural Representation Learning"
Bratu, Claudia. "Machine Learning of Crystal Formation Energies with Novel Structural Descriptors." Thesis, Linköpings universitet, Teoretisk Fysik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-143203.
Full textLadhams, Zieba Meagan. "Teaching and learning about reaction mechanisms in organic chemistry." University of Western Australia. School of Biomedical and Chemical Sciences, 2004. http://theses.library.uwa.edu.au/adt-WU2005.0035.
Full textMatta, Corrado. "A Field of Veiled Continuities : Studies in the Methodology and Theory of Educational Research." Doctoral thesis, Stockholms universitet, Institutionen för pedagogik och didaktik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-140475.
Full textAt the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 2: Manuscript.
(5929691), Asish Ghoshal. "Efficient Algorithms for Learning Combinatorial Structures from Limited Data." Thesis, 2019.
Find full textBooks on the topic "Broad Structural Representation Learning"
Nygaard, Taylor, and Jorie Lagerwey. Horrible White People. NYU Press, 2020. http://dx.doi.org/10.18574/nyu/9781479885459.001.0001.
Full textPapafragou, Anna, John C. Trueswell, and Lila R. Gleitman, eds. The Oxford Handbook of the Mental Lexicon. Oxford University Press, 2022. http://dx.doi.org/10.1093/oxfordhb/9780198845003.001.0001.
Full textBever, Thomas G. The Unity of Consciousness and the Consciousness of Unity. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190464783.003.0005.
Full textBook chapters on the topic "Broad Structural Representation Learning"
Cantoni, Virginio, Alessio Ferone, Ozlem Ozbudak, and Alfredo Petrosino. "Protein Structural Blocks Representation and Search through Unsupervised NN." In Artificial Neural Networks and Machine Learning – ICANN 2012, 515–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33266-1_64.
Full textChoi, Jun-Sik, Eunho Lee, and Heung-Il Suk. "Regional Abnormality Representation Learning in Structural MRI for AD/MCI Diagnosis." In Machine Learning in Medical Imaging, 64–72. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00919-9_8.
Full textYu, Bin, Xinhang Xu, Chao Wen, Yu Xie, and Chen Zhang. "Hierarchical Graph Representation Learning with Structural Attention for Graph Classification." In Artificial Intelligence, 473–84. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20500-2_39.
Full textZheng, Kai, Zhu-Hong You, Lei Wang, Yi-Ran Li, Yan-Bin Wang, and Han-Jing Jiang. "MISSIM: Improved miRNA-Disease Association Prediction Model Based on Chaos Game Representation and Broad Learning System." In Intelligent Computing Methodologies, 392–98. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26766-7_36.
Full textDutta, Saikat, Zixin Huang, and Sasa Misailovic. "SixthSense: Debugging Convergence Problems in Probabilistic Programs via Program Representation Learning." In Fundamental Approaches to Software Engineering, 123–44. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99429-7_7.
Full textde las Heras, Lluís-Pere, and Gemma Sánchez. "And-Or Graph Grammar for Architectural Floor Plan Representation, Learning and Recognition. A Semantic, Structural and Hierarchical Model." In Pattern Recognition and Image Analysis, 17–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21257-4_3.
Full textTomar, Dimpal, and Pradeep Tomar. "Artificial Intelligence-Based Knowledge Representation and Reasoning." In Impact of AI Technologies on Teaching, Learning, and Research in Higher Education, 134–49. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-4763-2.ch008.
Full textMbati, Lydia Sophia. "Capabilities-Based Transformative Online Learning Pedagogy for Social Justice." In Advances in Educational Marketing, Administration, and Leadership, 253–72. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-9108-5.ch014.
Full textMbati, Lydia Sophia. "Capabilities-Based Transformative Online Learning Pedagogy for Social Justice." In Research Anthology on Instilling Social Justice in the Classroom, 1175–94. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7706-6.ch067.
Full textHowson, Camille B. Kandiko, and Ian Kinchin. "Mapping the Doctorate." In Cases on Teaching Critical Thinking through Visual Representation Strategies, 446–65. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-5816-5.ch017.
Full textConference papers on the topic "Broad Structural Representation Learning"
Wang, Hu, Guansong Pang, Chunhua Shen, and Congbo Ma. "Unsupervised Representation Learning by Predicting Random Distances." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/408.
Full textChen, C. L. Philip. "Broad Learning System and its Structural Variations." In 2018 IEEE 16th International Symposium on Intelligent Systems and Informatics (SISY). IEEE, 2018. http://dx.doi.org/10.1109/sisy.2018.8524681.
Full textRossi, Ryan A., Nesreen K. Ahmed, Eunyee Koh, Sungchul Kim, Anup Rao, and Yasin Abbasi-Yadkori. "A Structural Graph Representation Learning Framework." In WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3336191.3371843.
Full textQuan, Tianhong, Ye Yuan, Youyi Song, Teng Zhou, and Jing Qin. "Fuzzy Structural Broad Learning for Breast Cancer Classification." In 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). IEEE, 2022. http://dx.doi.org/10.1109/isbi52829.2022.9761496.
Full textQuan, Tianhong, Ye Yuan, Youyi Song, Teng Zhou, and Jing Qin. "Fuzzy Structural Broad Learning for Breast Cancer Classification." In 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). IEEE, 2022. http://dx.doi.org/10.1109/isbi52829.2022.9761496.
Full textChen, Nenglun, Lingjie Liu, Zhiming Cui, Runnan Chen, Duygu Ceylan, Changhe Tu, and Wenping Wang. "Unsupervised Learning of Intrinsic Structural Representation Points." In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2020. http://dx.doi.org/10.1109/cvpr42600.2020.00914.
Full textLiu, Lin, Xin Li, William K. Cheung, and Chengcheng Xu. "A Structural Representation Learning for Multi-relational Networks." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/565.
Full textCarpenter, Justin, Janet Layne, Edoardo Serra, and Alfredo Cuzzocrea. "Detecting Botnet Nodes via Structural Node Representation Learning." In 2021 IEEE International Conference on Big Data (Big Data). IEEE, 2021. http://dx.doi.org/10.1109/bigdata52589.2021.9671728.
Full textYang, Mengyue, Furui Liu, Zhitang Chen, Xinwei Shen, Jianye Hao, and Jun Wang. "CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models." In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2021. http://dx.doi.org/10.1109/cvpr46437.2021.00947.
Full textChen, Xiaotian, Yuwang Wang, Xuejin Chen, and Wenjun Zeng. "S2R-DepthNet: Learning a Generalizable Depth-specific Structural Representation." In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2021. http://dx.doi.org/10.1109/cvpr46437.2021.00305.
Full textReports on the topic "Broad Structural Representation Learning"
Ustinova, Viktoriia O., Svitlana V. Shokaliuk, Iryna S. Mintii, and Andrey V. Pikilnyak. Modern techniques of organizing computer support for future teachers’ independent work in German language. [б. в.], September 2019. http://dx.doi.org/10.31812/123456789/3255.
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