Artigos de revistas sobre o tema "Computational Learning Sciences"
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Willcox, Karen. "Scientific Machine Learning". Aerospace Testing International 2020, n.º 2 (junho de 2020): 14. http://dx.doi.org/10.12968/s1478-2774(22)50190-8.
Texto completo da fonteFrank, Michael, Dimitris Drikakis e Vassilis Charissis. "Machine-Learning Methods for Computational Science and Engineering". Computation 8, n.º 1 (3 de março de 2020): 15. http://dx.doi.org/10.3390/computation8010015.
Texto completo da fonteBirhane, Abeba, e Olivia Guest. "Towards Decolonising Computational Sciences". Kvinder, Køn & Forskning, n.º 2 (8 de fevereiro de 2021): 60–73. http://dx.doi.org/10.7146/kkf.v29i2.124899.
Texto completo da fonteNick, Mitchel Res. "Learning Through Computational Modeling". Computers in the Schools 14, n.º 1-2 (4 de dezembro de 1997): 143–52. http://dx.doi.org/10.1300/j025v14n01_11.
Texto completo da fonteDodig-Crnkovic, G. "Natural morphological computation as foundation of learning to learn in humans, other living organisms, and intelligent machines". Philosophical Problems of Information Technologies and Cyberspace, n.º 1 (14 de julho de 2021): 4–34. http://dx.doi.org/10.17726/philit.2021.1.1.
Texto completo da fonteDodig-Crnkovic, Gordana. "Natural Morphological Computation as Foundation of Learning to Learn in Humans, Other Living Organisms, and Intelligent Machines". Philosophies 5, n.º 3 (1 de setembro de 2020): 17. http://dx.doi.org/10.3390/philosophies5030017.
Texto completo da fonteThiessen, Erik D. "What's statistical about learning? Insights from modelling statistical learning as a set of memory processes". Philosophical Transactions of the Royal Society B: Biological Sciences 372, n.º 1711 (5 de janeiro de 2017): 20160056. http://dx.doi.org/10.1098/rstb.2016.0056.
Texto completo da fonteSchaal, Stefan, Auke Ijspeert e Aude Billard. "Computational approaches to motor learning by imitation". Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 358, n.º 1431 (17 de fevereiro de 2003): 537–47. http://dx.doi.org/10.1098/rstb.2002.1258.
Texto completo da fonteChen, Jiming, e Diwakar Shukla. "Integration of machine learning with computational structural biology of plants". Biochemical Journal 479, n.º 8 (29 de abril de 2022): 921–28. http://dx.doi.org/10.1042/bcj20200942.
Texto completo da fonteRundo, Leonardo, Andrea Tangherloni e Carmelo Militello. "Artificial Intelligence Applied to Medical Imaging and Computational Biology". Applied Sciences 12, n.º 18 (8 de setembro de 2022): 9052. http://dx.doi.org/10.3390/app12189052.
Texto completo da fonteToivonen, Hannu. "Computational creativity beyond machine learning". Physics of Life Reviews 34-35 (dezembro de 2020): 52–53. http://dx.doi.org/10.1016/j.plrev.2020.06.007.
Texto completo da fonteOreski, Dijana. "Application of Machine Learning Methods for Data Analytics in Social Sciences". WSEAS TRANSACTIONS ON SYSTEMS 22 (7 de março de 2023): 69–72. http://dx.doi.org/10.37394/23202.2023.22.8.
Texto completo da fonteFernández, Jacqueline M., Mariela E. Zúñiga, María V. Rosas e Roberto A. Guerrero. "Experiences in Learning Problem-Solving through Computational Thinking". Journal of Computer Science and Technology 18, n.º 02 (9 de outubro de 2018): e15. http://dx.doi.org/10.24215/16666038.18.e15.
Texto completo da fonteCabrero-Holgueras, José, e Sergio Pastrana. "SoK: Privacy-Preserving Computation Techniques for Deep Learning". Proceedings on Privacy Enhancing Technologies 2021, n.º 4 (23 de julho de 2021): 139–62. http://dx.doi.org/10.2478/popets-2021-0064.
Texto completo da fonteGinestet, Cedric. "Semisupervised Learning for Computational Linguistics". Journal of the Royal Statistical Society: Series A (Statistics in Society) 172, n.º 3 (junho de 2009): 694. http://dx.doi.org/10.1111/j.1467-985x.2009.00595_2.x.
Texto completo da fontePerez, B., C. Castellanos e D. Correal. "Measuring the quality of the blended learning approach to teaching computational sciences". Journal of Physics: Conference Series 1587 (julho de 2020): 012021. http://dx.doi.org/10.1088/1742-6596/1587/1/012021.
Texto completo da fonteXi, Yue, Wenjing Jia, Qiguang Miao, Xiangzeng Liu, Xiaochen Fan e Jian Lou. "DyCC-Net: Dynamic Context Collection Network for Input-Aware Drone-View Object Detection". Remote Sensing 14, n.º 24 (13 de dezembro de 2022): 6313. http://dx.doi.org/10.3390/rs14246313.
Texto completo da fonteGuha Majumdar, Mrittunjoy. "Quantum 3.0: Quantum Learning, Quantum Heuristics and Beyond". Current Natural Sciences and Engineering 1, n.º 3 (29 de maio de 2024): 175–87. http://dx.doi.org/10.63015/3a-2425.1.3.
Texto completo da fonteGuha Majumdar, Mrittunjoy. "Quantum 3.0: Quantum Learning, Quantum Heuristics and Beyond". Current Natural Sciences and Engineering 1, n.º 3 (29 de maio de 2024): 175–87. http://dx.doi.org/10.63015/3a-2425.1.1.
Texto completo da fonteAmour, Idrissa S. "STACK for Computational Science, Mathematics and Engineering e-Learners". Tanzania Journal of Engineering and Technology 42, n.º 4 (23 de fevereiro de 2024): 69–80. http://dx.doi.org/10.52339/tjet.v42i4.825.
Texto completo da fonteKatai, Zoltan. "Promoting computational thinking of both sciences- and humanities-oriented students: an instructional and motivational design perspective". Educational Technology Research and Development 68, n.º 5 (3 de abril de 2020): 2239–61. http://dx.doi.org/10.1007/s11423-020-09766-5.
Texto completo da fonteAngermueller, Christof, Tanel Pärnamaa, Leopold Parts e Oliver Stegle. "Deep learning for computational biology". Molecular Systems Biology 12, n.º 7 (julho de 2016): 878. http://dx.doi.org/10.15252/msb.20156651.
Texto completo da fonteRosenfeld, Ariel, e Avshalom Elmalech. "Information Science Students’ Background and Data Science Competencies: An Exploratory Study". Journal of Education for Library and Information Science 64, n.º 4 (1 de outubro de 2023): 385–403. http://dx.doi.org/10.3138/jelis-2021-0076.
Texto completo da fonteKumala, Farida Nur, Arnelia Dwi Yasa, Adam Bin Haji Jait, Aji Prasetya Wibawa e Laily Hidayah. "Patterns of Computational Thinking Skills for Elementary Prospectives Teacher in Science Learning: Gender Analysis Studies". International Journal of Elementary Education 7, n.º 4 (28 de dezembro de 2023): 646–56. http://dx.doi.org/10.23887/ijee.v7i4.68611.
Texto completo da fonteBjorck, Johan, Brendan H. Rappazzo, Qinru Shi, Carrie Brown-Lima, Jennifer Dean, Angela Fuller e Carla Gomes. "Accelerating Ecological Sciences from Above: Spatial Contrastive Learning for Remote Sensing". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 17 (18 de maio de 2021): 14711–20. http://dx.doi.org/10.1609/aaai.v35i17.17728.
Texto completo da fonteFilatova, Darya, Charles El-Nouty e Uladzislau Punko. "HIGH-THROUGHPUT DEEP LEARNING ALGORITHM FOR DIAGNOSIS AND DEFECTS CLASSIFICATION OF WATERPROOFING MEMBRANES". International Journal for Computational Civil and Structural Engineering 16, n.º 2 (26 de junho de 2020): 26–38. http://dx.doi.org/10.22337/2587-9618-2020-16-2-26-38.
Texto completo da fonteR.D., Dhaniya, e Dr Umamaheswari K.M. "Brain Tumor Analysis Empowered with Machine Learning and Deep Learning: A Comprehensive Review with its Recent Computational Techniques". Webology 19, n.º 1 (20 de janeiro de 2022): 764–79. http://dx.doi.org/10.14704/web/v19i1/web19054.
Texto completo da fonteLee, Chia-Jung, Chi-Jen Lu e Shi-Chun Tsai. "Extracting Computational Entropy and Learning Noisy Linear Functions". IEEE Transactions on Information Theory 57, n.º 8 (agosto de 2011): 5485–96. http://dx.doi.org/10.1109/tit.2011.2158897.
Texto completo da fonteGhulam, Ali, Rahu Sikander e Farman Ali. "AI and Machine Learning-based practices in various domains: A Survey". VAWKUM Transactions on Computer Sciences 10, n.º 1 (30 de junho de 2022): 21–41. http://dx.doi.org/10.21015/vtcs.v10i1.1257.
Texto completo da fontePau, Danilo Pietro, e Fabrizio Maria Aymone. "Mathematical Formulation of Learning and Its Computational Complexity for Transformers’ Layers". Eng 5, n.º 1 (21 de dezembro de 2023): 34–50. http://dx.doi.org/10.3390/eng5010003.
Texto completo da fonteChanda, Pritam, Eduardo Costa, Jie Hu, Shravan Sukumar, John Van Hemert e Rasna Walia. "Information Theory in Computational Biology: Where We Stand Today". Entropy 22, n.º 6 (6 de junho de 2020): 627. http://dx.doi.org/10.3390/e22060627.
Texto completo da fonteLI, Suiqing, Xinling CHEN, Yuzhu ZHAI, Yijie ZHANG, Zhixing ZHANG e Chunliang FENG. "The computational and neural substrates underlying social learning". Advances in Psychological Science 29, n.º 4 (2021): 677. http://dx.doi.org/10.3724/sp.j.1042.2021.00677.
Texto completo da fonteXavier, Rita, e Leandro Nunes de Castro. "On the use of evolutionary and swarm intelligence algorithms in transfer learning approaches: a review". International Journal of Biosensors & Bioelectronics 8, n.º 2 (26 de dezembro de 2023): 58–64. http://dx.doi.org/10.15406/ijbsbe.2023.08.00235.
Texto completo da fonteYanti, Yuli, Diah Rizki Nur Kalifah e Nurul Hidayah. "Implementing Computational Thinking Skills in Socio Scientific Issue (SSI) of Force Material Around Us at Elementary School". E3S Web of Conferences 482 (2024): 04001. http://dx.doi.org/10.1051/e3sconf/202448204001.
Texto completo da fonteMerino-Armero, José Miguel, José Antonio González-Calero, Ramón Cózar-Gutiérrez e Javier del Olmo-Muñoz. "Unplugged Activities in Cross-Curricular Teaching: Effect on Sixth Graders’ Computational Thinking and Learning Outcomes". Multimodal Technologies and Interaction 6, n.º 2 (28 de janeiro de 2022): 13. http://dx.doi.org/10.3390/mti6020013.
Texto completo da fonteBoldea, Afrodita L. "The impact of teaching computational astronomy on the development of students' computer skills". EPJ Web of Conferences 200 (2019): 02001. http://dx.doi.org/10.1051/epjconf/201920002001.
Texto completo da fonteLevites, Yulia A., Myles Joshua T. Tan, Akshita Gupta, Jamie L. Fermin, Samuel P. Border, Sanjay Jain, John Tomaszewski, Yulia A. Levites Strekalova e Pinaki Sarder. "89 Bridging Cell Biology and Engineering Sciences: Interdisciplinary Team-based Training in Computational Pathology". Journal of Clinical and Translational Science 7, s1 (abril de 2023): 25. http://dx.doi.org/10.1017/cts.2023.172.
Texto completo da fonteEl Alami, Marc, Nicolas Casel e Denis Zampunieris. "An architecture for e‐learning system with computational intelligence". Electronic Library 26, n.º 3 (6 de junho de 2008): 318–28. http://dx.doi.org/10.1108/02640470810879473.
Texto completo da fonteHowley, Iris K., e Carolyn Penstein Rose. "Towards Careful Practices for Automated Linguistic Analysis of Group Learning". Journal of Learning Analytics 3, n.º 3 (19 de dezembro de 2016): 239–62. http://dx.doi.org/10.18608/jla.2016.33.12.
Texto completo da fonteSikora, Riyaz, e Michael J. Shaw. "A Computational Study of Distributed Rule Learning". Information Systems Research 7, n.º 2 (junho de 1996): 189–97. http://dx.doi.org/10.1287/isre.7.2.189.
Texto completo da fonteCzech, Sławomir. "Evaluating the Role of Machine Learning in Economics: A Cutting-Edge Addition or Rhetorical Device?" Studies in Logic, Grammar and Rhetoric 68, n.º 1 (1 de dezembro de 2023): 279–93. http://dx.doi.org/10.2478/slgr-2023-0014.
Texto completo da fonteGago, Eduardo. "Teaching and Learning Computational Mathematics with Intensive Application of the Virtual Campus". WSEAS TRANSACTIONS ON ADVANCES in ENGINEERING EDUCATION 20 (13 de outubro de 2023): 81–90. http://dx.doi.org/10.37394/232010.2023.20.11.
Texto completo da fonteNiazai, Shafiullah, Ariana Abdul Rahimzai e Hamza Atifnigar. "Applications of MATLAB in Natural Sciences: A Comprehensive Review". European Journal of Theoretical and Applied Sciences 1, n.º 5 (1 de setembro de 2023): 1006–15. http://dx.doi.org/10.59324/ejtas.2023.1(5).87.
Texto completo da fonteXiao, Zhifeng, Linjun Qian, Weiping Shao, Xiaowei Tan e Kai Wang. "Axis Learning for Orientated Objects Detection in Aerial Images". Remote Sensing 12, n.º 6 (12 de março de 2020): 908. http://dx.doi.org/10.3390/rs12060908.
Texto completo da fontePeel, Amanda, Troy D. Sadler e Patricia Friedrichsen. "Using Unplugged Computational Thinking to Scaffold Natural Selection Learning". American Biology Teacher 83, n.º 2 (1 de fevereiro de 2021): 112–17. http://dx.doi.org/10.1525/abt.2021.83.2.112.
Texto completo da fonteMitelman, Amichai, Beverly Yang, Alon Urlainis e Davide Elmo. "Coupling Geotechnical Numerical Analysis with Machine Learning for Observational Method Projects". Geosciences 13, n.º 7 (28 de junho de 2023): 196. http://dx.doi.org/10.3390/geosciences13070196.
Texto completo da fonteWu, Linfeng, Huajun Wang e Huiqing Wang. "A Lightweight Conditional Convolutional Neural Network for Hyperspectral Image Classification". Photogrammetric Engineering & Remote Sensing 89, n.º 7 (1 de julho de 2023): 413–23. http://dx.doi.org/10.14358/pers.22-00130r2.
Texto completo da fonteAlexandrov, Theodore. "Spatial Metabolomics and Imaging Mass Spectrometry in the Age of Artificial Intelligence". Annual Review of Biomedical Data Science 3, n.º 1 (20 de julho de 2020): 61–87. http://dx.doi.org/10.1146/annurev-biodatasci-011420-031537.
Texto completo da fonteLodi, Michael, e Simone Martini. "Computational Thinking, Between Papert and Wing". Science & Education 30, n.º 4 (28 de abril de 2021): 883–908. http://dx.doi.org/10.1007/s11191-021-00202-5.
Texto completo da fonteGarcía-Martínez, Inmaculada, José María Fernández-Batanero, Jose Fernández-Cerero e Samuel P. León. "Analysing the Impact of Artificial Intelligence and Computational Sciences on Student Performance: Systematic Review and Meta-analysis". Journal of New Approaches in Educational Research 12, n.º 1 (15 de janeiro de 2023): 171. http://dx.doi.org/10.7821/naer.2023.1.1240.
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