Статті в журналах з теми "Computational Learning Sciences"
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся з топ-50 статей у журналах для дослідження на тему "Computational Learning Sciences".
Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.
Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.
Переглядайте статті в журналах для різних дисциплін та оформлюйте правильно вашу бібліографію.
Willcox, Karen. "Scientific Machine Learning." Aerospace Testing International 2020, no. 2 (June 2020): 14. http://dx.doi.org/10.12968/s1478-2774(22)50190-8.
Frank, Michael, Dimitris Drikakis, and Vassilis Charissis. "Machine-Learning Methods for Computational Science and Engineering." Computation 8, no. 1 (March 3, 2020): 15. http://dx.doi.org/10.3390/computation8010015.
Birhane, Abeba, and Olivia Guest. "Towards Decolonising Computational Sciences." Kvinder, Køn & Forskning, no. 2 (February 8, 2021): 60–73. http://dx.doi.org/10.7146/kkf.v29i2.124899.
Nick, Mitchel Res. "Learning Through Computational Modeling." Computers in the Schools 14, no. 1-2 (December 4, 1997): 143–52. http://dx.doi.org/10.1300/j025v14n01_11.
Dodig-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, no. 1 (July 14, 2021): 4–34. http://dx.doi.org/10.17726/philit.2021.1.1.
Dodig-Crnkovic, Gordana. "Natural Morphological Computation as Foundation of Learning to Learn in Humans, Other Living Organisms, and Intelligent Machines." Philosophies 5, no. 3 (September 1, 2020): 17. http://dx.doi.org/10.3390/philosophies5030017.
Thiessen, 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, no. 1711 (January 5, 2017): 20160056. http://dx.doi.org/10.1098/rstb.2016.0056.
Schaal, Stefan, Auke Ijspeert, and Aude Billard. "Computational approaches to motor learning by imitation." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 358, no. 1431 (February 17, 2003): 537–47. http://dx.doi.org/10.1098/rstb.2002.1258.
Chen, Jiming, and Diwakar Shukla. "Integration of machine learning with computational structural biology of plants." Biochemical Journal 479, no. 8 (April 29, 2022): 921–28. http://dx.doi.org/10.1042/bcj20200942.
Rundo, Leonardo, Andrea Tangherloni, and Carmelo Militello. "Artificial Intelligence Applied to Medical Imaging and Computational Biology." Applied Sciences 12, no. 18 (September 8, 2022): 9052. http://dx.doi.org/10.3390/app12189052.
Toivonen, Hannu. "Computational creativity beyond machine learning." Physics of Life Reviews 34-35 (December 2020): 52–53. http://dx.doi.org/10.1016/j.plrev.2020.06.007.
Oreski, Dijana. "Application of Machine Learning Methods for Data Analytics in Social Sciences." WSEAS TRANSACTIONS ON SYSTEMS 22 (March 7, 2023): 69–72. http://dx.doi.org/10.37394/23202.2023.22.8.
Fernández, Jacqueline M., Mariela E. Zúñiga, María V. Rosas, and Roberto A. Guerrero. "Experiences in Learning Problem-Solving through Computational Thinking." Journal of Computer Science and Technology 18, no. 02 (October 9, 2018): e15. http://dx.doi.org/10.24215/16666038.18.e15.
Cabrero-Holgueras, José, and Sergio Pastrana. "SoK: Privacy-Preserving Computation Techniques for Deep Learning." Proceedings on Privacy Enhancing Technologies 2021, no. 4 (July 23, 2021): 139–62. http://dx.doi.org/10.2478/popets-2021-0064.
Ginestet, Cedric. "Semisupervised Learning for Computational Linguistics." Journal of the Royal Statistical Society: Series A (Statistics in Society) 172, no. 3 (June 2009): 694. http://dx.doi.org/10.1111/j.1467-985x.2009.00595_2.x.
Perez, B., C. Castellanos, and D. Correal. "Measuring the quality of the blended learning approach to teaching computational sciences." Journal of Physics: Conference Series 1587 (July 2020): 012021. http://dx.doi.org/10.1088/1742-6596/1587/1/012021.
Xi, Yue, Wenjing Jia, Qiguang Miao, Xiangzeng Liu, Xiaochen Fan, and Jian Lou. "DyCC-Net: Dynamic Context Collection Network for Input-Aware Drone-View Object Detection." Remote Sensing 14, no. 24 (December 13, 2022): 6313. http://dx.doi.org/10.3390/rs14246313.
Guha Majumdar, Mrittunjoy. "Quantum 3.0: Quantum Learning, Quantum Heuristics and Beyond." Current Natural Sciences and Engineering 1, no. 3 (May 29, 2024): 175–87. http://dx.doi.org/10.63015/3a-2425.1.3.
Guha Majumdar, Mrittunjoy. "Quantum 3.0: Quantum Learning, Quantum Heuristics and Beyond." Current Natural Sciences and Engineering 1, no. 3 (May 29, 2024): 175–87. http://dx.doi.org/10.63015/3a-2425.1.1.
Amour, Idrissa S. "STACK for Computational Science, Mathematics and Engineering e-Learners." Tanzania Journal of Engineering and Technology 42, no. 4 (February 23, 2024): 69–80. http://dx.doi.org/10.52339/tjet.v42i4.825.
Katai, Zoltan. "Promoting computational thinking of both sciences- and humanities-oriented students: an instructional and motivational design perspective." Educational Technology Research and Development 68, no. 5 (April 3, 2020): 2239–61. http://dx.doi.org/10.1007/s11423-020-09766-5.
Angermueller, Christof, Tanel Pärnamaa, Leopold Parts, and Oliver Stegle. "Deep learning for computational biology." Molecular Systems Biology 12, no. 7 (July 2016): 878. http://dx.doi.org/10.15252/msb.20156651.
Rosenfeld, Ariel, and Avshalom Elmalech. "Information Science Students’ Background and Data Science Competencies: An Exploratory Study." Journal of Education for Library and Information Science 64, no. 4 (October 1, 2023): 385–403. http://dx.doi.org/10.3138/jelis-2021-0076.
Kumala, Farida Nur, Arnelia Dwi Yasa, Adam Bin Haji Jait, Aji Prasetya Wibawa, and Laily Hidayah. "Patterns of Computational Thinking Skills for Elementary Prospectives Teacher in Science Learning: Gender Analysis Studies." International Journal of Elementary Education 7, no. 4 (December 28, 2023): 646–56. http://dx.doi.org/10.23887/ijee.v7i4.68611.
Bjorck, Johan, Brendan H. Rappazzo, Qinru Shi, Carrie Brown-Lima, Jennifer Dean, Angela Fuller, and Carla Gomes. "Accelerating Ecological Sciences from Above: Spatial Contrastive Learning for Remote Sensing." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 17 (May 18, 2021): 14711–20. http://dx.doi.org/10.1609/aaai.v35i17.17728.
Filatova, Darya, Charles El-Nouty, and Uladzislau Punko. "HIGH-THROUGHPUT DEEP LEARNING ALGORITHM FOR DIAGNOSIS AND DEFECTS CLASSIFICATION OF WATERPROOFING MEMBRANES." International Journal for Computational Civil and Structural Engineering 16, no. 2 (June 26, 2020): 26–38. http://dx.doi.org/10.22337/2587-9618-2020-16-2-26-38.
R.D., Dhaniya, and Dr Umamaheswari K.M. "Brain Tumor Analysis Empowered with Machine Learning and Deep Learning: A Comprehensive Review with its Recent Computational Techniques." Webology 19, no. 1 (January 20, 2022): 764–79. http://dx.doi.org/10.14704/web/v19i1/web19054.
Lee, Chia-Jung, Chi-Jen Lu, and Shi-Chun Tsai. "Extracting Computational Entropy and Learning Noisy Linear Functions." IEEE Transactions on Information Theory 57, no. 8 (August 2011): 5485–96. http://dx.doi.org/10.1109/tit.2011.2158897.
Ghulam, Ali, Rahu Sikander, and Farman Ali. "AI and Machine Learning-based practices in various domains: A Survey." VAWKUM Transactions on Computer Sciences 10, no. 1 (June 30, 2022): 21–41. http://dx.doi.org/10.21015/vtcs.v10i1.1257.
Pau, Danilo Pietro, and Fabrizio Maria Aymone. "Mathematical Formulation of Learning and Its Computational Complexity for Transformers’ Layers." Eng 5, no. 1 (December 21, 2023): 34–50. http://dx.doi.org/10.3390/eng5010003.
Chanda, Pritam, Eduardo Costa, Jie Hu, Shravan Sukumar, John Van Hemert, and Rasna Walia. "Information Theory in Computational Biology: Where We Stand Today." Entropy 22, no. 6 (June 6, 2020): 627. http://dx.doi.org/10.3390/e22060627.
LI, Suiqing, Xinling CHEN, Yuzhu ZHAI, Yijie ZHANG, Zhixing ZHANG, and Chunliang FENG. "The computational and neural substrates underlying social learning." Advances in Psychological Science 29, no. 4 (2021): 677. http://dx.doi.org/10.3724/sp.j.1042.2021.00677.
Xavier, Rita, and 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, no. 2 (December 26, 2023): 58–64. http://dx.doi.org/10.15406/ijbsbe.2023.08.00235.
Yanti, Yuli, Diah Rizki Nur Kalifah, and 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.
Merino-Armero, José Miguel, José Antonio González-Calero, Ramón Cózar-Gutiérrez, and Javier del Olmo-Muñoz. "Unplugged Activities in Cross-Curricular Teaching: Effect on Sixth Graders’ Computational Thinking and Learning Outcomes." Multimodal Technologies and Interaction 6, no. 2 (January 28, 2022): 13. http://dx.doi.org/10.3390/mti6020013.
Boldea, 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.
Levites, Yulia A., Myles Joshua T. Tan, Akshita Gupta, Jamie L. Fermin, Samuel P. Border, Sanjay Jain, John Tomaszewski, Yulia A. Levites Strekalova, and Pinaki Sarder. "89 Bridging Cell Biology and Engineering Sciences: Interdisciplinary Team-based Training in Computational Pathology." Journal of Clinical and Translational Science 7, s1 (April 2023): 25. http://dx.doi.org/10.1017/cts.2023.172.
El Alami, Marc, Nicolas Casel, and Denis Zampunieris. "An architecture for e‐learning system with computational intelligence." Electronic Library 26, no. 3 (June 6, 2008): 318–28. http://dx.doi.org/10.1108/02640470810879473.
Howley, Iris K., and Carolyn Penstein Rose. "Towards Careful Practices for Automated Linguistic Analysis of Group Learning." Journal of Learning Analytics 3, no. 3 (December 19, 2016): 239–62. http://dx.doi.org/10.18608/jla.2016.33.12.
Sikora, Riyaz, and Michael J. Shaw. "A Computational Study of Distributed Rule Learning." Information Systems Research 7, no. 2 (June 1996): 189–97. http://dx.doi.org/10.1287/isre.7.2.189.
Czech, Sławomir. "Evaluating the Role of Machine Learning in Economics: A Cutting-Edge Addition or Rhetorical Device?" Studies in Logic, Grammar and Rhetoric 68, no. 1 (December 1, 2023): 279–93. http://dx.doi.org/10.2478/slgr-2023-0014.
Gago, Eduardo. "Teaching and Learning Computational Mathematics with Intensive Application of the Virtual Campus." WSEAS TRANSACTIONS ON ADVANCES in ENGINEERING EDUCATION 20 (October 13, 2023): 81–90. http://dx.doi.org/10.37394/232010.2023.20.11.
Niazai, Shafiullah, Ariana Abdul Rahimzai, and Hamza Atifnigar. "Applications of MATLAB in Natural Sciences: A Comprehensive Review." European Journal of Theoretical and Applied Sciences 1, no. 5 (September 1, 2023): 1006–15. http://dx.doi.org/10.59324/ejtas.2023.1(5).87.
Xiao, Zhifeng, Linjun Qian, Weiping Shao, Xiaowei Tan, and Kai Wang. "Axis Learning for Orientated Objects Detection in Aerial Images." Remote Sensing 12, no. 6 (March 12, 2020): 908. http://dx.doi.org/10.3390/rs12060908.
Peel, Amanda, Troy D. Sadler, and Patricia Friedrichsen. "Using Unplugged Computational Thinking to Scaffold Natural Selection Learning." American Biology Teacher 83, no. 2 (February 1, 2021): 112–17. http://dx.doi.org/10.1525/abt.2021.83.2.112.
Mitelman, Amichai, Beverly Yang, Alon Urlainis, and Davide Elmo. "Coupling Geotechnical Numerical Analysis with Machine Learning for Observational Method Projects." Geosciences 13, no. 7 (June 28, 2023): 196. http://dx.doi.org/10.3390/geosciences13070196.
Wu, Linfeng, Huajun Wang, and Huiqing Wang. "A Lightweight Conditional Convolutional Neural Network for Hyperspectral Image Classification." Photogrammetric Engineering & Remote Sensing 89, no. 7 (July 1, 2023): 413–23. http://dx.doi.org/10.14358/pers.22-00130r2.
Alexandrov, Theodore. "Spatial Metabolomics and Imaging Mass Spectrometry in the Age of Artificial Intelligence." Annual Review of Biomedical Data Science 3, no. 1 (July 20, 2020): 61–87. http://dx.doi.org/10.1146/annurev-biodatasci-011420-031537.
Lodi, Michael, and Simone Martini. "Computational Thinking, Between Papert and Wing." Science & Education 30, no. 4 (April 28, 2021): 883–908. http://dx.doi.org/10.1007/s11191-021-00202-5.
García-Martínez, Inmaculada, José María Fernández-Batanero, Jose Fernández-Cerero, and 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, no. 1 (January 15, 2023): 171. http://dx.doi.org/10.7821/naer.2023.1.1240.