Alex Dunn 个人学术档案 - 学术资源搜索

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Anubhav JainLawrence Berkeley National Lab在 lbl.gov 的电子邮件经过验证
Kristin Aslaug Persson (nee Einarsdott...Department of Materials Science and Engineering, UC Berkeley在 berkeley.edu 的电子邮件经过验证
Gerbrand CederProfessor of Materials Science and Engineering在 berkeley.edu 的电子邮件经过验证
John DagdelenDoctorate, University of California, Berkeley在 berkeley.edu 的电子邮件经过验证
Amalie TrewarthaSenior Research Scientist, Toyota Research Institute在 tri.global 的电子邮件经过验证
G. Jeffrey SnyderNorthwestern University在 northwestern.edu 的电子邮件经过验证
Maxwell DyllaNorthwestern University在 u.northwestern.edu 的电子邮件经过验证
Vahe TshitoyanGoogle ATAP在 google.com 的电子邮件经过验证
Olga KononovaResearcher/Developer在 syngenta.com 的电子邮件经过验证
Ziqin RongMIT Computer Science Master, Materials Science PhD在 mit.edu 的电子邮件经过验证
Leigh WestonLawrence Berkeley National Laboratory在 engineering.ucsb.edu 的电子邮件经过验证
Ian T. FosterUniversity of Chicago and Argonne National Laboratory在 anl.gov 的电子邮件经过验证
Nils E. R. ZimmermannUniversity of Stuttgart在 tuhh.de 的电子邮件经过验证
M. AstaUniversity of California, Sandia National Laboratories, Northwestern University在 berkeley.edu 的电子邮件经过验证
Saurabh BajajMicron Technology Inc在 lbl.gov 的电子邮件经过验证
Logan WardArgonne National Laboratory, Data Science and Learning Division在 anl.gov 的电子邮件经过验证
Alireza FaghaniniaMaterials Postdoctoral Fellow, Lawrence Berkeley National Laboratory在 lbl.gov 的电子邮件经过验证
Joseph MontoyaToyota Research Institute在 tri.global 的电子邮件经过验证
Kyle BystromApplied Physics PhD Student, Harvard University在 g.harvard.edu 的电子邮件经过验证
Alex GanoseImperial College London在 imperial.ac.uk 的电子邮件经过验证

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Alex Dunn

University of California, Berkeley

在 lbl.gov 的电子邮件经过验证 - 首页

machine learning computational materials science


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Unsupervised word embeddings capture latent knowledge from materials science literature V Tshitoyan, J Dagdelen, L Weston, A Dunn, Z Rong, O Kononova, ... Nature 571 (7763), 95-98, 2019	946	2019
Matminer: An open source toolkit for materials data mining L Ward, A Dunn, A Faghaninia, NER Zimmermann, S Bajaj, Q Wang, ... Computational Materials Science 152, 60-69, 2018	668	2018
Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm A Dunn, Q Wang, A Ganose, D Dopp, A Jain npj Computational Materials 6 (1), 138, 2020	211	2020
A critical examination of compound stability predictions from machine-learned formation energies CJ Bartel, A Trewartha, Q Wang, A Dunn, A Jain, G Ceder npj computational materials 6 (1), 97, 2020	152	2020
Quantifying the advantage of domain-specific pre-training on named entity recognition tasks in materials science A Trewartha, N Walker, H Huo, S Lee, K Cruse, J Dagdelen, A Dunn, ... Patterns 3 (4), 2022	93	2022
Structured information extraction from complex scientific text with fine-tuned large language models A Dunn, J Dagdelen, N Walker, S Lee, AS Rosen, G Ceder, K Persson, ... arXiv preprint arXiv:2212.05238, 2022	91	2022
Electropneumatic Towing Stabilizer System AR Dunn US Patent App. 14/055,729, 2015	52	2015
Experimental validation of high thermoelectric performance in RECuZnP 2 predicted by high-throughput DFT calculations JH Pöhls, S Chanakian, J Park, AM Ganose, A Dunn, N Friesen, ... Materials Horizons 8 (1), 209-215, 2021	44	2021
Machine-learning rationalization and prediction of solid-state synthesis conditions H Huo, CJ Bartel, T He, A Trewartha, A Dunn, B Ouyang, A Jain, G Ceder Chemistry of Materials 34 (16), 7323-7336, 2022	40	2022
Machine learning chemical guidelines for engineering electronic structures in half-heusler thermoelectric materials MT Dylla, A Dunn, S Anand, A Jain, GJ Snyder Research, 2020	40	2020
Structured information extraction from scientific text with large language models J Dagdelen, A Dunn, S Lee, N Walker, AS Rosen, G Ceder, KA Persson, ... Nature Communications 15 (1), 1418, 2024	32	2024
Gapped metals as thermoelectric materials revealed by high-throughput screening F Ricci, A Dunn, A Jain, GM Rignanese, G Hautier Journal of Materials Chemistry A 8 (34), 17579-17594, 2020	26	2020
Rocketsled: a software library for optimizing high-throughput computational searches A Dunn, J Brenneck, A Jain Journal of Physics: Materials 2 (3), 034002, 2019	22	2019
The impact of domain-specific pre-training on named entity recognition tasks in materials science N Walker, A Trewartha, H Huo, S Lee, K Cruse, J Dagdelen, A Dunn, ... Available at SSRN 3950755, 2021	20	2021
5 Algorithms for materials discovery J Dagdelen, A Dunn Accelerated Materials Discovery: How to Use Artificial Intelligence to Speed …, 2022		2022

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