Artykuły w czasopismach na temat „Computational Learning Sciences”
Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych
Sprawdź 50 najlepszych artykułów w czasopismach naukowych na temat „Computational Learning Sciences”.
Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.
Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.
Przeglądaj artykuły w czasopismach z różnych dziedzin i twórz odpowiednie bibliografie.
Willcox, Karen. "Scientific Machine Learning". Aerospace Testing International 2020, nr 2 (czerwiec 2020): 14. http://dx.doi.org/10.12968/s1478-2774(22)50190-8.
Pełny tekst źródłaFrank, Michael, Dimitris Drikakis i Vassilis Charissis. "Machine-Learning Methods for Computational Science and Engineering". Computation 8, nr 1 (3.03.2020): 15. http://dx.doi.org/10.3390/computation8010015.
Pełny tekst źródłaBirhane, Abeba, i Olivia Guest. "Towards Decolonising Computational Sciences". Kvinder, Køn & Forskning, nr 2 (8.02.2021): 60–73. http://dx.doi.org/10.7146/kkf.v29i2.124899.
Pełny tekst źródłaNick, Mitchel Res. "Learning Through Computational Modeling". Computers in the Schools 14, nr 1-2 (4.12.1997): 143–52. http://dx.doi.org/10.1300/j025v14n01_11.
Pełny tekst źródłaDodig-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, nr 1 (14.07.2021): 4–34. http://dx.doi.org/10.17726/philit.2021.1.1.
Pełny tekst źródłaDodig-Crnkovic, Gordana. "Natural Morphological Computation as Foundation of Learning to Learn in Humans, Other Living Organisms, and Intelligent Machines". Philosophies 5, nr 3 (1.09.2020): 17. http://dx.doi.org/10.3390/philosophies5030017.
Pełny tekst źródłaThiessen, 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, nr 1711 (5.01.2017): 20160056. http://dx.doi.org/10.1098/rstb.2016.0056.
Pełny tekst źródłaSchaal, Stefan, Auke Ijspeert i Aude Billard. "Computational approaches to motor learning by imitation". Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 358, nr 1431 (17.02.2003): 537–47. http://dx.doi.org/10.1098/rstb.2002.1258.
Pełny tekst źródłaChen, Jiming, i Diwakar Shukla. "Integration of machine learning with computational structural biology of plants". Biochemical Journal 479, nr 8 (29.04.2022): 921–28. http://dx.doi.org/10.1042/bcj20200942.
Pełny tekst źródłaRundo, Leonardo, Andrea Tangherloni i Carmelo Militello. "Artificial Intelligence Applied to Medical Imaging and Computational Biology". Applied Sciences 12, nr 18 (8.09.2022): 9052. http://dx.doi.org/10.3390/app12189052.
Pełny tekst źródłaToivonen, Hannu. "Computational creativity beyond machine learning". Physics of Life Reviews 34-35 (grudzień 2020): 52–53. http://dx.doi.org/10.1016/j.plrev.2020.06.007.
Pełny tekst źródłaOreski, Dijana. "Application of Machine Learning Methods for Data Analytics in Social Sciences". WSEAS TRANSACTIONS ON SYSTEMS 22 (7.03.2023): 69–72. http://dx.doi.org/10.37394/23202.2023.22.8.
Pełny tekst źródłaFernández, Jacqueline M., Mariela E. Zúñiga, María V. Rosas i Roberto A. Guerrero. "Experiences in Learning Problem-Solving through Computational Thinking". Journal of Computer Science and Technology 18, nr 02 (9.10.2018): e15. http://dx.doi.org/10.24215/16666038.18.e15.
Pełny tekst źródłaCabrero-Holgueras, José, i Sergio Pastrana. "SoK: Privacy-Preserving Computation Techniques for Deep Learning". Proceedings on Privacy Enhancing Technologies 2021, nr 4 (23.07.2021): 139–62. http://dx.doi.org/10.2478/popets-2021-0064.
Pełny tekst źródłaGinestet, Cedric. "Semisupervised Learning for Computational Linguistics". Journal of the Royal Statistical Society: Series A (Statistics in Society) 172, nr 3 (czerwiec 2009): 694. http://dx.doi.org/10.1111/j.1467-985x.2009.00595_2.x.
Pełny tekst źródłaPerez, B., C. Castellanos i D. Correal. "Measuring the quality of the blended learning approach to teaching computational sciences". Journal of Physics: Conference Series 1587 (lipiec 2020): 012021. http://dx.doi.org/10.1088/1742-6596/1587/1/012021.
Pełny tekst źródłaXi, Yue, Wenjing Jia, Qiguang Miao, Xiangzeng Liu, Xiaochen Fan i Jian Lou. "DyCC-Net: Dynamic Context Collection Network for Input-Aware Drone-View Object Detection". Remote Sensing 14, nr 24 (13.12.2022): 6313. http://dx.doi.org/10.3390/rs14246313.
Pełny tekst źródłaGuha Majumdar, Mrittunjoy. "Quantum 3.0: Quantum Learning, Quantum Heuristics and Beyond". Current Natural Sciences and Engineering 1, nr 3 (29.05.2024): 175–87. http://dx.doi.org/10.63015/3a-2425.1.3.
Pełny tekst źródłaGuha Majumdar, Mrittunjoy. "Quantum 3.0: Quantum Learning, Quantum Heuristics and Beyond". Current Natural Sciences and Engineering 1, nr 3 (29.05.2024): 175–87. http://dx.doi.org/10.63015/3a-2425.1.1.
Pełny tekst źródłaAmour, Idrissa S. "STACK for Computational Science, Mathematics and Engineering e-Learners". Tanzania Journal of Engineering and Technology 42, nr 4 (23.02.2024): 69–80. http://dx.doi.org/10.52339/tjet.v42i4.825.
Pełny tekst źródłaKatai, Zoltan. "Promoting computational thinking of both sciences- and humanities-oriented students: an instructional and motivational design perspective". Educational Technology Research and Development 68, nr 5 (3.04.2020): 2239–61. http://dx.doi.org/10.1007/s11423-020-09766-5.
Pełny tekst źródłaAngermueller, Christof, Tanel Pärnamaa, Leopold Parts i Oliver Stegle. "Deep learning for computational biology". Molecular Systems Biology 12, nr 7 (lipiec 2016): 878. http://dx.doi.org/10.15252/msb.20156651.
Pełny tekst źródłaRosenfeld, Ariel, i Avshalom Elmalech. "Information Science Students’ Background and Data Science Competencies: An Exploratory Study". Journal of Education for Library and Information Science 64, nr 4 (1.10.2023): 385–403. http://dx.doi.org/10.3138/jelis-2021-0076.
Pełny tekst źródłaKumala, Farida Nur, Arnelia Dwi Yasa, Adam Bin Haji Jait, Aji Prasetya Wibawa i Laily Hidayah. "Patterns of Computational Thinking Skills for Elementary Prospectives Teacher in Science Learning: Gender Analysis Studies". International Journal of Elementary Education 7, nr 4 (28.12.2023): 646–56. http://dx.doi.org/10.23887/ijee.v7i4.68611.
Pełny tekst źródłaBjorck, Johan, Brendan H. Rappazzo, Qinru Shi, Carrie Brown-Lima, Jennifer Dean, Angela Fuller i Carla Gomes. "Accelerating Ecological Sciences from Above: Spatial Contrastive Learning for Remote Sensing". Proceedings of the AAAI Conference on Artificial Intelligence 35, nr 17 (18.05.2021): 14711–20. http://dx.doi.org/10.1609/aaai.v35i17.17728.
Pełny tekst źródłaFilatova, Darya, Charles El-Nouty i Uladzislau Punko. "HIGH-THROUGHPUT DEEP LEARNING ALGORITHM FOR DIAGNOSIS AND DEFECTS CLASSIFICATION OF WATERPROOFING MEMBRANES". International Journal for Computational Civil and Structural Engineering 16, nr 2 (26.06.2020): 26–38. http://dx.doi.org/10.22337/2587-9618-2020-16-2-26-38.
Pełny tekst źródłaR.D., Dhaniya, i Dr Umamaheswari K.M. "Brain Tumor Analysis Empowered with Machine Learning and Deep Learning: A Comprehensive Review with its Recent Computational Techniques". Webology 19, nr 1 (20.01.2022): 764–79. http://dx.doi.org/10.14704/web/v19i1/web19054.
Pełny tekst źródłaLee, Chia-Jung, Chi-Jen Lu i Shi-Chun Tsai. "Extracting Computational Entropy and Learning Noisy Linear Functions". IEEE Transactions on Information Theory 57, nr 8 (sierpień 2011): 5485–96. http://dx.doi.org/10.1109/tit.2011.2158897.
Pełny tekst źródłaGhulam, Ali, Rahu Sikander i Farman Ali. "AI and Machine Learning-based practices in various domains: A Survey". VAWKUM Transactions on Computer Sciences 10, nr 1 (30.06.2022): 21–41. http://dx.doi.org/10.21015/vtcs.v10i1.1257.
Pełny tekst źródłaPau, Danilo Pietro, i Fabrizio Maria Aymone. "Mathematical Formulation of Learning and Its Computational Complexity for Transformers’ Layers". Eng 5, nr 1 (21.12.2023): 34–50. http://dx.doi.org/10.3390/eng5010003.
Pełny tekst źródłaChanda, Pritam, Eduardo Costa, Jie Hu, Shravan Sukumar, John Van Hemert i Rasna Walia. "Information Theory in Computational Biology: Where We Stand Today". Entropy 22, nr 6 (6.06.2020): 627. http://dx.doi.org/10.3390/e22060627.
Pełny tekst źródłaLI, Suiqing, Xinling CHEN, Yuzhu ZHAI, Yijie ZHANG, Zhixing ZHANG i Chunliang FENG. "The computational and neural substrates underlying social learning". Advances in Psychological Science 29, nr 4 (2021): 677. http://dx.doi.org/10.3724/sp.j.1042.2021.00677.
Pełny tekst źródłaXavier, Rita, i 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, nr 2 (26.12.2023): 58–64. http://dx.doi.org/10.15406/ijbsbe.2023.08.00235.
Pełny tekst źródłaYanti, Yuli, Diah Rizki Nur Kalifah i 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.
Pełny tekst źródłaMerino-Armero, José Miguel, José Antonio González-Calero, Ramón Cózar-Gutiérrez i Javier del Olmo-Muñoz. "Unplugged Activities in Cross-Curricular Teaching: Effect on Sixth Graders’ Computational Thinking and Learning Outcomes". Multimodal Technologies and Interaction 6, nr 2 (28.01.2022): 13. http://dx.doi.org/10.3390/mti6020013.
Pełny tekst źródłaBoldea, 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.
Pełny tekst źródłaLevites, Yulia A., Myles Joshua T. Tan, Akshita Gupta, Jamie L. Fermin, Samuel P. Border, Sanjay Jain, John Tomaszewski, Yulia A. Levites Strekalova i Pinaki Sarder. "89 Bridging Cell Biology and Engineering Sciences: Interdisciplinary Team-based Training in Computational Pathology". Journal of Clinical and Translational Science 7, s1 (kwiecień 2023): 25. http://dx.doi.org/10.1017/cts.2023.172.
Pełny tekst źródłaEl Alami, Marc, Nicolas Casel i Denis Zampunieris. "An architecture for e‐learning system with computational intelligence". Electronic Library 26, nr 3 (6.06.2008): 318–28. http://dx.doi.org/10.1108/02640470810879473.
Pełny tekst źródłaHowley, Iris K., i Carolyn Penstein Rose. "Towards Careful Practices for Automated Linguistic Analysis of Group Learning". Journal of Learning Analytics 3, nr 3 (19.12.2016): 239–62. http://dx.doi.org/10.18608/jla.2016.33.12.
Pełny tekst źródłaSikora, Riyaz, i Michael J. Shaw. "A Computational Study of Distributed Rule Learning". Information Systems Research 7, nr 2 (czerwiec 1996): 189–97. http://dx.doi.org/10.1287/isre.7.2.189.
Pełny tekst źródłaCzech, Sławomir. "Evaluating the Role of Machine Learning in Economics: A Cutting-Edge Addition or Rhetorical Device?" Studies in Logic, Grammar and Rhetoric 68, nr 1 (1.12.2023): 279–93. http://dx.doi.org/10.2478/slgr-2023-0014.
Pełny tekst źródłaGago, Eduardo. "Teaching and Learning Computational Mathematics with Intensive Application of the Virtual Campus". WSEAS TRANSACTIONS ON ADVANCES in ENGINEERING EDUCATION 20 (13.10.2023): 81–90. http://dx.doi.org/10.37394/232010.2023.20.11.
Pełny tekst źródłaNiazai, Shafiullah, Ariana Abdul Rahimzai i Hamza Atifnigar. "Applications of MATLAB in Natural Sciences: A Comprehensive Review". European Journal of Theoretical and Applied Sciences 1, nr 5 (1.09.2023): 1006–15. http://dx.doi.org/10.59324/ejtas.2023.1(5).87.
Pełny tekst źródłaXiao, Zhifeng, Linjun Qian, Weiping Shao, Xiaowei Tan i Kai Wang. "Axis Learning for Orientated Objects Detection in Aerial Images". Remote Sensing 12, nr 6 (12.03.2020): 908. http://dx.doi.org/10.3390/rs12060908.
Pełny tekst źródłaPeel, Amanda, Troy D. Sadler i Patricia Friedrichsen. "Using Unplugged Computational Thinking to Scaffold Natural Selection Learning". American Biology Teacher 83, nr 2 (1.02.2021): 112–17. http://dx.doi.org/10.1525/abt.2021.83.2.112.
Pełny tekst źródłaMitelman, Amichai, Beverly Yang, Alon Urlainis i Davide Elmo. "Coupling Geotechnical Numerical Analysis with Machine Learning for Observational Method Projects". Geosciences 13, nr 7 (28.06.2023): 196. http://dx.doi.org/10.3390/geosciences13070196.
Pełny tekst źródłaWu, Linfeng, Huajun Wang i Huiqing Wang. "A Lightweight Conditional Convolutional Neural Network for Hyperspectral Image Classification". Photogrammetric Engineering & Remote Sensing 89, nr 7 (1.07.2023): 413–23. http://dx.doi.org/10.14358/pers.22-00130r2.
Pełny tekst źródłaAlexandrov, Theodore. "Spatial Metabolomics and Imaging Mass Spectrometry in the Age of Artificial Intelligence". Annual Review of Biomedical Data Science 3, nr 1 (20.07.2020): 61–87. http://dx.doi.org/10.1146/annurev-biodatasci-011420-031537.
Pełny tekst źródłaLodi, Michael, i Simone Martini. "Computational Thinking, Between Papert and Wing". Science & Education 30, nr 4 (28.04.2021): 883–908. http://dx.doi.org/10.1007/s11191-021-00202-5.
Pełny tekst źródłaGarcía-Martínez, Inmaculada, José María Fernández-Batanero, Jose Fernández-Cerero i 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, nr 1 (15.01.2023): 171. http://dx.doi.org/10.7821/naer.2023.1.1240.
Pełny tekst źródła