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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	R. Jin, Zhong, B., Ma, L., Hashemi, A. & Ding, L. (2019) Integrating bim with building performance analysis in project life-cycle , Automation in Construction, 106, 102861. https://doi.org/10.1016/j.autcon.2019.102861

	R. L. Johns (2014) Augmented Materiality Modelling with Material Indeterminacy , Fabricate, 216–223

	R. Rael, and V. San Fratello (2017) Clay Bodies: Crafting the Future with 3D Printing , Architectural Design 87 (6) 92–97

	R.Mancini, A.J.Dix and S.Levialdi (1997) Dealing with Undo , Proceedings of Interact ’97, Chapman and Hall, Sydney, Australia

	Rabardel, P and Bourmaud, G (2003) From computer to instrument system: a developmental perspective , Interacting with Computers 15(2003), pp. 665-691

	Rabardel, P. and G. Bourmauda (2003) From computer to instrument system: a developmental perspective , Interacting with Computers, 2003. 15: p. 665-691

	Rabardel, P. and G.Bourmauda (2003) From computer to instrument system: a developmental perspective , Interacting with Computers, 2003.(15), 665-691

	Rachael Luck (2018) Inclusive Design and Making in Practice: Bringing Bodily Experience in Close Contact With Making , Design Studies 54: 96–119

	Rada, RR and Bicknell, BE (1989) Ranking Documents with Thesaurus , Journal of the American Society for Information Science, 40(5), pp. 304-311

	Radford A, Metz L and Chintala S (2015) Unsupervised representation learning with deep convolutional generative adversarial networks, , http://arxiv.org/pdf/1511.06434v2 (2015).

	Radford, A, Metz, L and Chintala, S (2015) Unsupervised representation learning with deep convolutional generative adversarial networks , arXiv preprint arXiv:1511.06434, 1, pp. 1-5

	Radford, Alec, Luke Metz, and Soumith Chintala (2015) Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , ICLR (International Conference on Learning Representations). arXiv:1511.06434

	Radford, Alec, Luke Metz, and Soumith Chintala (2015) Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , arXiv preprint. arXiv:1511.06434

	Radinsky, J., Milz, D., Zellner, M., Pudlock, K., Witek, C., Hoch, C., & Lyons, L. (2017) How planners and stakeholders learn with visualization tools: using learning sciences methods to examine planning processes , Journal of Environmental Planning and Management, 60(7), 1296–1323

	Radomir, M., Przemyslaw, P. (1996) Visual Models of Plants Interacting with Their Environment , 23rd annual conference on Computer graphics and interactive techniques, ACM. (pp. 39741). The Association for Computing Machinery (ACM)

	Rael R. and San Fratello V. (2017) Clay bodies: crafting the future with 3D printing , Archit Design; 87(6): 92–97

	Rael, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., & Liu, P. J. (2020) Exploring the Limits of Transfer Learning with a United Text-to-text Transformer , Journal of Machine Learning Research 21, Available at: https://doi.org/1.4855/arXiv.191.1683.

	Rael, R and San Fratello, V (2017) Clay Bodies: Crafting the Futures with 3D Printing , Architectural Design, 87(6), pp. 92-97

	Rael, R and San Fratello, V (2017) Clay Bodies: Crafting the Future with 3D Printing , AD, Architectural Design, 3D Printed Body Architecture, 87(6), pp. 92-97

	Rael, Ronald, and Virginia San Fratello (2017) Clay Bodies: Crafting the Future with 3D Printing , Architectural Design 87 (6): 92–97. https://www.doi.org/10.1002/ad.2243

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