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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	Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio (2014) Generative Adversarial Nets , Advances in Neural InformationProcessing Systems, 2672–80

	M Mirza. and S. Osindero (2014) Conditional Generative Adversarial Nets , ArXiv Preprint

	Mirza, M and Osindero, S (2014) Conditional generative adversarial nets , arXiv preprint arXiv:1411.1784, https://arxiv.org/pdf/1411.1784v1.pdf, pp. 1-7

	Mirza, M. & Osindero, S. (2014) Conditional generative adversarial nets , ArXiv, vol. abs/1411.1784

	Mirza, M. & Osindero, S. (2014) Conditional generative adversarial nets , arXiv preprint arXiv: 1411.1784

	Mirza, M. and Osindero, S. (2014) Conditional generative adversarial nets. , arXiv preprint arXiv, 1411.1784, pp. 1-7

	Mirza, M., & Osindero, S. (2014) Conditional Generative Adversarial Nets , ArXiv:1411.1784 [Cs, Stat]. http://arxiv.org/abs/1411.1784

	Mirza, M., Osindero, S. (2014) Conditional Generative Adversarial Nets , Conference on Neural Information Processing Systems(NIPS).arXiv:1411.1784 https://doi.org/10.48550/arXiv.1411.1784"

	Mirza, Mehdi, and Simon Osindero (2014) Conditional Generative Adversarial Nets , arXiv preprint. arXiv:1411.1784

	Mirza, Mehdi, and Simon Osindero. (2014) Conditional generative adversarial nets , arXiv:1411.1784

	Alani, M. and Al-Kaseem, B. (2021) Fill in the Blanks: Deep Convolutional Generative Adversarial Networks to Investigate the Virtual Design Space of Historical Islamic Patterns in Proceedings of the 9th ASCAAD Conference , Cairo, Egypt [Virtual Conference], pp. 614-621. Available at: http://papers.cumincad.org/data/works/att/ascaad2021_093.pdf (Accessed 6 March 2022)

	Ali Jahanian, Lucy Chai, and Phillip Isola (2020) On the ‘Steerability’ of Generative Adversarial Networks , International Conference onLearning Representations

	Allen-Dumas, M.R. et al. (2022) Generative adversarial networks for ensemble projections of future urban morphology , Proceedings of the 5th ACM SIGSPATIAL International Workshop on Advances in Resilient and Intelligent Cities. SIGSPATIAL '22: The 30th International Conference on Advances in Geographic Information Systems, Seattle Washington: ACM, pp. 1-6

	Arjovsky, Martin, Soumith Chintala, and Léon Bottou (2017) Wasserstein Generative Adversarial Networks , Proceedings of the 34th International Conference on Machine Learning (PMLR), Sydney, Australia, 7–9 August 2017, 214–223. PMLR

	Cai, JC and Zhu, HZ (2019) Lung image segmentation by generative adversarial networks , Proceedings of SPIE 2019

	Campo, M. (2021) Architecture, Language and Ai-language, Attentional Generative Adversarial Networks (attngan) and Architecture Design , Proceedings of the 26th CAADRIA Conference(Vol. 1, pp. 211-22)

	Chan, Eric R., Connor Z. Lin, Matthew A. Chan, Koki Nagano, Boxiao Pan, Shalini De Mello, Orazio Gallo, et al (2021) Efficient Geometry- Aware 3D Generative Adversarial Networks , arXiv

	Chan, Y. E., & Spaeth, A. B. (2020) Architectural Visualisation with Conditional Generative Adversarial Networks - What machines read in architectural sketches. , Education and research in Computer Aided Architectural Design in Europe (eCAADe) Conference 2020, Berlin, Germany

	Chan, Y. H., & Spaeth, B. (2020) Architectural Visualisation with Conditional Generative Adversarial Networks (cgan): What Machines Read in Architectural Sketches. , Proceedings of the 38th International Conference on Education and Research in Computer Aided Architectural Design in Europe (ECAADe),Volume 2.Available at: https://doi.org/1.52842/conf.ecaade.22.2.299

	Choi, EM (2017) Generating Multi-label Discrete Patient Records using Generative Adversarial Networks , Proceedings of Machine Learning for Healthcare, pp. 1-20

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