Architectural Plasticity: The Aesthetics of Neural Sampling von Koh, Immanuel

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Architectural sampling: three possible preconditions for machine learning architectural forms von Koh, Immanuel

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Discrete Sampling: There is No Object or Field … Just Statistical Digital Patterns von Koh, Immanuel

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Architectural and Social ‘Word Forms’ Slippage with Deep Learning von Koh, Immanuel

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3D Diffusion or 3D Disfiguration? von Koh, Immanuel

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Voxel Substitutional Sampling: Generative Machine Learning for Architectural Design von Koh, Immanuel

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Associative Synthesis with Deep Neural Networks for Architectural Design von Koh, Immanuel

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Voxel Synthesis for Architectural Design von Koh, Immanuel

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Conjugated Materiality – Reinstating Material Circularity via Digital Twins von Garg, Nipun, Huang, Sheng-Yang

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(In)visible Cities: What Generative Algorithms Tell Us About Our Collective Memory Schema von Rico Carranza, Eduardo, Huang, Sheng-Yang, Besems, Julian, Gao, Wanqi

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Voxel Synthesis for Generative Design von Khokhlov, Matvey, Koh, Immanuel, Huang, Jeffrey

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Architectural Sampling: A Formal Basis for Machine-Learnable Architecture von Koh, Immanuel Chee Beng

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Patterns of Pediatric Malaria Incidence and Outcomes in Kasungu, Malawi in 2016 von Kim, Byungchan, Chang, Sohyun, Shin, Min Jae, Hong, Prescott, Lee, George, Koh, Min Jung, Anaborne, Immanuel H., Lee, Donghoon, Chung, Paul S., Talama, George, Nyirenda, Thomas

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