Cumincad : CUMINCAD References : Search Results

CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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	Illeris, K. (2003) Towards a contemporary and comprehensive theory of learning , Int. J. of Lifelong Education, 22(3), pp. 396-406

	Injadat M, Salo F, Nassif AB, et al (2018) Bayesian optimization with machine learning algorithms towards anomaly detection , Proceedings of IEEE Global Communications Conference, Abu Dhabi, UAE, 09–13 December 2018, pp. 1–6

	Inoue, K. and Urahama, K. (2000) Learning of view-invariant pattern recognizer with temporal context , Pattern Recognition 33: 1665-1674

	Ioannidou, A, Chatzilari, E, Nikolopoulos, S and Kompatsiaris, I (2017) Deep learning advances in computer vision with 3d data: A survey , ACM Computing Surveys (CSUR), 50(2), pp. 1-38

	Ioannis Chatzikonstantinou and Sevil Sariyildiz (2016) Approximation of Simulation-Derived Visual Comfort Indicators in Office Spaces: A Comparative Study in Machine Learning , Architectural Science Review 59 (4): 307–22. https://doi.org/10.1080/00038628.2015.1072705

	Ioffe, S and Szegedy, C (2015) Batch normalization: Accelerating deep network training by reducing internal covariate shift , Proceedings of the 32nd International Conference on Machine Learning, Lille

	Ioffe, S. & Szegedy, C. (2015) Batch normalization: Accelerating deep network training by reducing internal covariate shift , International Conference on Machine Learning

	Iordanova, I., Forgues, D., Tidafi, T., Jemtrud, M. & Maria-Farah, L. (2010) Interdisciplinary Team Learning in the Context of Integrated Design Studio , Paper presented at the Construction Research Congress 2010 (CRC 2010), 8-11 mai, Banff, Canada

	Isaac Mangual, Garret Wood-Sternburgh, Larisa Sherbakova, Misri Patel, and Ryan Craney (2022) Digital Digital Fabrication Fabrication: Remote Collaborative Teaching and Learning in Advanced Fabrication , ACSA 110th Annual Meeting, Virtual Conference, May 18-20

	Isanovic, H and Çolakoglu, B (2018) Developing a Methodology for Learning BIM through Education-Practice Collaboration , Proceedings of the 36th eCAADe Conference - Volume 1, Lodz, Poland, pp. 241-246

	Ishaan, G., Faruk, A., Martin, A., Vincent, D., Aaron, C. (2017) Improved Training of Wasserstein GANs , Machine Learning. arXiv:1704.00028. Available at: https://doi.org/10.48550/arXiv.1704.00028

	Ito, M., Horst, H., Bittanti, M., Boyd, D., Herr-Stephenson, B., Lange, P. G., et al. (2008) Living and learning with new media: Summary of findings from the digital youth project ,

	Iturrate, I, Hallundb?k, E, ?stergaard, M and Savarimuthu, TR (2017) Learning and correcting robot trajectory keypoints from a single demonstration , Control, Automation and Robotics (ICCAR), 2017 3rd International Conference, pp. 52-59

	J. Luo and H. Li (2020) Dynamic Experience Replay , Proceedings of the Conference on Robot Learning in Proceedings of Machine Learning Research, 100:1191-1200. Available from https://proceedings.mlr.press/v100/luo20a. html

	J. P. Duarte (1991) MIT-Miyagi 2002: an experiment in using grammars for remote collaboration , Collaborative Design and Learning: competence building for innovation, J. Bento, J. P. Duarte, M. Heitor, W. J. Mitchell, Eds, Praeger, Westport CT, 1991, pp. 79-115

	Jabbar AIA and Felicia P. (2015) Gameplay engagement and learning in game-based learning: a systematic review , Rev Educ Res; 85(4): 740–779

	Jabi, W. and Alymani, A. (2020) Graph Machine Learning Using 3D Topological Models , SimAUD, (May), pp. 427-434

	Jabi, W., T. Hall, K. Passerini, C. Borcea, and Q. Jones (2008) Exporting the studio model of learning , Proceedings of the 26th conference on education and research in computer aided architectural design in Europe (in publication). Antwerp, Belgium: ECAADE

	Jack Breen (1998 ) Learning from the (in)visible city, Design media experiments in an educational setting , Delft University of Technology, 010 Publishers, Rotterdam

	Jack Ngarambe, Indira Adilkhanova, Beatha Uwiragiye, and Geun Young Yun (2022) A Review on the Current Usage of Machine Learning Tools for Daylighting Design and Control , Building and Environment 223 (September): 109507. https://doi.org/10.1016/j.buildenv.2022.109507

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