Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science von Agrawal, Ankit, Choudhary, Alok

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Classification of sentiment reviews using n-gram machine learning approach von Tripathy, Abinash, Agrawal, Ankit, Rath, Santanu Kumar

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Deep materials informatics: Applications of deep learning in materials science von Agrawal, Ankit, Choudhary, Alok

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Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning von Jha, Dipendra, Choudhary, Kamal, Tavazza, Francesca, Liao, Wei-keng, Choudhary, Alok, Campbell, Carelyn, Agrawal, Ankit

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A general-purpose machine learning framework for predicting properties of inorganic materials von Ward, Logan, Agrawal, Ankit, Choudhary, Alok, Wolverton, Christopher

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A kinetic study of pyrolysis and combustion of microalgae Chlorella vulgaris using thermo-gravimetric analysis von Agrawal, Ankit, Chakraborty, Saikat

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Localized Surface Plasmon Resonance in Semiconductor Nanocrystals von Agrawal, Ankit, Cho, Shin Hum, Zandi, Omid, Ghosh, Sandeep, Johns, Robert W, Milliron, Delia J

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Recent advances and applications of deep learning methods in materials science von Choudhary, Kamal, DeCost, Brian, Chen, Chi, Jain, Anubhav, Tavazza, Francesca, Cohn, Ryan, Park, Cheol Woo, Choudhary, Alok, Agrawal, Ankit, Billinge, Simon J. L., Holm, Elizabeth, Ong, Shyue Ping, Wolverton, Chris

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Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data von Gupta, Vishu, Choudhary, Kamal, Tavazza, Francesca, Campbell, Carelyn, Liao, Wei-keng, Choudhary, Alok, Agrawal, Ankit

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An approach for evaluating residual capacity of reinforced concrete beams exposed to fire von Kodur, V.K.R., Agrawal, Ankit

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ElemNet: Deep Learning the Chemistry of Materials From Only Elemental Composition von Jha, Dipendra, Ward, Logan, Paul, Arindam, Liao, Wei-keng, Choudhary, Alok, Wolverton, Chris, Agrawal, Ankit

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Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets von Yang, Zijiang, Yabansu, Yuksel C., Al-Bahrani, Reda, Liao, Wei-keng, Choudhary, Alok N., Kalidindi, Surya R., Agrawal, Ankit

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Microstructural Materials Design Via Deep Adversarial Learning Methodology von Yang, Zijiang, Li, Xiaolin, Catherine Brinson, L, Choudhary, Alok N, Chen, Wei, Agrawal, Ankit

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Establishing structure-property localization linkages for elastic deformation of three-dimensional high contrast composites using deep learning approaches von Yang, Zijiang, Yabansu, Yuksel C., Jha, Dipendra, Liao, Wei-keng, Choudhary, Alok N., Kalidindi, Surya R., Agrawal, Ankit

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A predictive machine learning approach for microstructure optimization and materials design von Liu, Ruoqian, Kumar, Abhishek, Chen, Zhengzhang, Agrawal, Ankit, Sundararaghavan, Veera, Choudhary, Alok

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Enabling deeper learning on big data for materials informatics applications von Jha, Dipendra, Gupta, Vishu, Ward, Logan, Yang, Zijiang, Wolverton, Christopher, Foster, Ian, Liao, Wei-keng, Choudhary, Alok, Agrawal, Ankit

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Impacts of surface depletion on the plasmonic properties of doped semiconductor nanocrystals von Zandi, Omid, Agrawal, Ankit, Shearer, Alex B., Reimnitz, Lauren C., Dahlman, Clayton J., Staller, Corey M., Milliron, Delia J.

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Influence of Shape on the Surface Plasmon Resonance of Tungsten Bronze Nanocrystals von Mattox, Tracy M, Bergerud, Amy, Agrawal, Ankit, Milliron, Delia J

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The Interplay of Shape and Crystalline Anisotropies in Plasmonic Semiconductor Nanocrystals von Kim, Jongwook, Agrawal, Ankit, Krieg, Franziska, Bergerud, Amy, Milliron, Delia J

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Predictive analytics for crystalline materials: bulk modulus von Furmanchuk, Al'ona, Agrawal, Ankit, Choudhary, Alok

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