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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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67%; open Cutler, M., T.J. Walsh, and J.P. How (2015) Find in CUMINCAD Real-world reinforcement learning via multifidelity simulators , IEEE Transactions on Robotics 31 (3): 655–671
67%; open Denton, Emily, Soumith Chintala, Arthur Szlam, and Rob Fergus (2015) Find in CUMINCAD Deep Generative Image Models Using a Laplacian Pyramid of Adversarial Networks , ArXiv:1506.05751 [Cs], June. http://arxiv.org/abs/1506.05751
67%; open Domingos, P (2015) Find in CUMINCAD The Master Algorithm: how the quest for machine learning will remake our world. , Basic Books
67%; open Domingos, P. (2015) Find in CUMINCAD The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World , New York: Basic Books. ISBN: 978-0-4650-6570-7
67%; open Domingos, Pedro (2015) Find in CUMINCAD The Master Algorithm. How the Quest for the Ultimate Learning Machine will Remake Our World , Basic Books, New York
67%; open Duvenaud D., Maclaurin D., Aguilera-Iparraguirre J. et al. (2015) Find in CUMINCAD Convolutional networks on graphs for learning molecular fingerprints , Proceedings of the 28th international conference on neural information processing systems (NIPS), Montreal, QC, Canada, 7–12 December 2015, vol. 2
67%; open El-Zanfaly, D. (2015) Find in CUMINCAD [I3] Imitation, iteration and improvisation: Embodied interaction in making and learning , Design Studies, 41, pp. 79-109
67%; open El-Zanfaly, D. (2015) Find in CUMINCAD Imitation, Iteration and Improvisation: Embodied interaction in making and learning , Design Studies, 41, Part A, 79–109
67%; open El-Zanfaly, D. (2015) Find in CUMINCAD Imitation, Iteration and Improvisation: Embodied Interaction in Making and Learning , Design Studies, 41, 79–109
67%; open El-Zanfaly, Dina (2015) Find in CUMINCAD Imitation, Iteration and Improvisation: Embodied Interaction in Making and Learning , Design Studies 41 (A): 79–109. doi:10.1016/j.destud.2015.09.002
67%; open El-Zanfaly, Dina (2015) Find in CUMINCAD Imitation, Iteration and Improvisation: Embodied Interaction in Making and Learning , Design Studies 41 (A): 79–109. doi:10.1016/j.destud.2015.09.002
67%; open Eloy, S, Dias, MS, Lopes, P and Vilar, E (2015) Find in CUMINCAD Multimedia technologies in Architecture and Engineering: exploring an engaged interaction within curriculums , Fonseca,, D and Redondo, E (eds), Handbook of Research on Applied E-Learning in Engineering and Architecture Education, IGI Global, pp. 368-402.
67%; open Elsayed, K and Fioravanti, A (2015) Find in CUMINCAD Digitally fabricated housing: tracking the evolution through two decades , Living and Learning: Research for a Better Built Environment: 49th International Conference of the Architectural Science Association, Melbourne, pp. 999-1008
67%; open Fabien Lotte, and Camille Jeunet (2015) Find in CUMINCAD Towards Improved BCI based on Human Learning Principles , The 3rd International Winter Conference on Brain-Computer Interface. 1-4
67%; open Flynn, J.; Neulander, I.; Philbin,J.; Snavely, N. (2015) Find in CUMINCAD DeepStereo: Learning to Predict New views from the World’s Imagery , arXiv
67%; open Galperina, Marina (2015) Find in CUMINCAD Is Google’s Deep Dream Art? , Hopes&Fears, July 14, 2015. http://www.hopesandfears.com/hopes/culture/is-this-art/215039-deep-dream-google-art
67%; open Galperina, Marina (2015) Find in CUMINCAD Is Google’s Deep Dream Art? , Hopes&Fears, July 14, 2015. http://www.hopesandfears.com/hopes/culture/is-this-art/215039-deep-dream-google-art
67%; open Gregor, K., Danihelka, I., Graves, A., Rezende, D. & Wierstra, D. (2015) Find in CUMINCAD Draw: A recurrent neural network for image generation , International Conference on Machine Learning
67%; open Hall, L. (2015) Find in CUMINCAD Building resilience for lifelong learning , Fine print, 38(2), 18-22
67%; open Haryanto, T., Pratama, A., Suhartanto, H., Murni, A., Kusmardi, K. & Pidanic, J. (2020) Find in CUMINCAD Multipatch-GLCM for Texture Feature Extraction on Classification of the Colon Histopathology Images using Deep Neural Network with GPU Acceleration , Journal of Computer Science, 16(3), 280–294. https://doi.org/10.3844/jcssp.2020.280.294Hassani, M. M., Wittel, F. K., Hering, S., & Herrmann, H. J. (2015). Rheological model for wood. Computer Methods in Applied Mechanics and Engineering, 283, 1032–1060. https://doi.org/10.1016/j.cma.2014.10.031

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