Risultati della ricerca - Jason Hattrick-Simpers

Kernel learning assisted synthesis condition exploration for ternary spinel di Yutong Liu, Mehrad Ansari, Robert Black, Jason Hattrick-Simpers

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LLM4Mat-bench: benchmarking large language models for materials property prediction di Andre Niyongabo Rubungo, Kangming Li, Jason Hattrick-Simpers, Adji Bousso Dieng

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Why big data and compute are not necessarily the path to big materials science di Naohiro Fujinuma, Brian DeCost, Jason Hattrick-Simpers, Samuel E. Lofland

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A critical examination of robustness and generalizability of machine learning prediction of materials properties di Kangming Li, Brian DeCost, Kamal Choudhary, Michael Greenwood, Jason Hattrick-Simpers

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High- superconductor candidates proposed by machine learning di Siwoo Lee, Jason Hattrick-Simpers, Young-June Kim, O Anatole von Lilienfeld

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Exploiting redundancy in large materials datasets for efficient machine learning with less data di Kangming Li, Daniel Persaud, Kamal Choudhary, Brian DeCost, Michael Greenwood, Jason Hattrick-Simpers

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Publisher Correction: Exploiting redundancy in large materials datasets for efficient machine learning with less data di Kangming Li, Daniel Persaud, Kamal Choudhary, Brian DeCost, Michael Greenwood, Jason Hattrick-Simpers

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Exploring the limitations of kNN noisy feature detection and recovery for self-driving labs di Qiuyu Shi, Kangming Li, Yao Fehlis, Runze Zhang, Daniel Persaud, Robert Black, Jason Hattrick-Simpers

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Bayesian assessment of commonly used equivalent circuit models for corrosion analysis in electrochemical impedance spectroscopy di Runze Zhang, Debashish Sur, Kangming Li, Julia Witt, Robert Black, Alexander Whittingham, John R. Scully, Jason Hattrick-Simpers

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Characterization data of an (AlFeNiTiVZr)1-xCrx multi-principal element alloy continuous composition spread library di Benjamin Ruiz-Yi, Travis Williams, Jonathan Kenneth Bunn, Fang Ren, Naila Al Hasan, Ichiro Takeuchi, Jason Hattrick-Simpers, Apurva Mehta

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Probing out-of-distribution generalization in machine learning for materials di Kangming Li, Andre Niyongabo Rubungo, Xiangyun Lei, Daniel Persaud, Kamal Choudhary, Brian DeCost, Adji Bousso Dieng, Jason Hattrick-Simpers

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Design criteria for single-phase non-equiatomic refractory multiprincipal element alloys from the Nb-Ti-Zr system di Sebastian Lech, Jason Hattrick-Simpers, Elaf A. Anber, Michael J. Waters, Howie Joress, Debashish Sur, Emily Holcombe, James M. Rondinelli, John R. Scully, Mitra L. Taheri

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Integrated High‐Throughput and Machine Learning Methods to Accelerate Discovery of Molten Salt Corrosion‐Resistant Alloys di Yafei Wang, Bonita Goh, Phalgun Nelaturu, Thien Duong, Najlaa Hassan, Raphaelle David, Michael Moorehead, Santanu Chaudhuri, Adam Creuziger, Jason Hattrick‐Simpers, Dan J. Thoma, Kumar Sridharan, Adrien Couet

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On-the-fly closed-loop materials discovery via Bayesian active learning di A. Gilad Kusne, Heshan Yu, Changming Wu, Huairuo Zhang, Jason Hattrick-Simpers, Brian DeCost, Suchismita Sarker, Corey Oses, Cormac Toher, Stefano Curtarolo, Albert V. Davydov, Ritesh Agarwal, Leonid A. Bendersky, Mo Li, Apurva Mehta, Ichiro Takeuchi

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JARVIS-Leaderboard: a large scale benchmark of materials design methods di Kamal Choudhary, Daniel Wines, Kangming Li, Kevin F. Garrity, Vishu Gupta, Aldo H. Romero, Jaron T. Krogel, Kayahan Saritas, Addis Fuhr, Panchapakesan Ganesh, Paul R. C. Kent, Keqiang Yan, Yuchao Lin, Shuiwang Ji, Ben Blaiszik, Patrick Reiser, Pascal Friederich, Ankit Agrawal, Pratyush Tiwary, Eric Beyerle, Peter Minch, Trevor David Rhone, Ichiro Takeuchi, Robert B. Wexler, Arun Mannodi-Kanakkithodi, Elif Ertekin, Avanish Mishra, Nithin Mathew, Mitchell Wood, Andrew Dale Rohskopf, Jason Hattrick-Simpers, Shih-Han Wang, Luke E. K. Achenie, Hongliang Xin, Maureen Williams, Adam J. Biacchi, Francesca Tavazza

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