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For: Bystrom K, Kozinsky B. CIDER: An Expressive, Nonlocal Feature Set for Machine Learning Density Functionals with Exact Constraints. J Chem Theory Comput 2022;18:2180-2192. [PMID: 35235322 DOI: 10.1021/acs.jctc.1c00904] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Number Cited by Other Article(s)
1
Khan D, Price AJA, Huang B, Ach ML, von Lilienfeld OA. Adapting hybrid density functionals with machine learning. SCIENCE ADVANCES 2025;11:eadt7769. [PMID: 39888985 PMCID: PMC11784814 DOI: 10.1126/sciadv.adt7769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2024] [Accepted: 01/03/2025] [Indexed: 02/02/2025]
2
Thiemann FL, O'Neill N, Kapil V, Michaelides A, Schran C. Introduction to machine learning potentials for atomistic simulations. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2024;37:073002. [PMID: 39577092 DOI: 10.1088/1361-648x/ad9657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2024] [Accepted: 11/22/2024] [Indexed: 11/24/2024]
3
Bystrom K, Falletta S, Kozinsky B. Training Machine-Learned Density Functionals on Band Gaps. J Chem Theory Comput 2024;20:7516-7532. [PMID: 39178337 DOI: 10.1021/acs.jctc.4c00999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/25/2024]
4
Voss J. Machine learning for accuracy in density functional approximations. J Comput Chem 2024;45:1829-1845. [PMID: 38668453 DOI: 10.1002/jcc.27366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 02/16/2024] [Accepted: 03/25/2024] [Indexed: 07/21/2024]
5
Sahoo SJ, Xu Q, Lei X, Staros D, Iyer GR, Rubenstein B, Suryanarayana P, Medford AJ. Self-Consistent Convolutional Density Functional Approximations: Application to Adsorption at Metal Surfaces. Chemphyschem 2024;25:e202300688. [PMID: 38421371 DOI: 10.1002/cphc.202300688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 02/23/2024] [Accepted: 02/25/2024] [Indexed: 03/02/2024]
6
Chen Z, Yang W. Development of a machine learning finite-range nonlocal density functional. J Chem Phys 2024;160:014105. [PMID: 38180254 DOI: 10.1063/5.0179149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 12/12/2023] [Indexed: 01/06/2024]  Open
7
Riemelmoser S, Verdi C, Kaltak M, Kresse G. Machine Learning Density Functionals from the Random-Phase Approximation. J Chem Theory Comput 2023;19:7287-7299. [PMID: 37800677 PMCID: PMC10601474 DOI: 10.1021/acs.jctc.3c00848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Indexed: 10/07/2023]
8
Remme R, Kaczun T, Scheurer M, Dreuw A, Hamprecht FA. KineticNet: Deep learning a transferable kinetic energy functional for orbital-free density functional theory. J Chem Phys 2023;159:144113. [PMID: 37830452 DOI: 10.1063/5.0158275] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 09/14/2023] [Indexed: 10/14/2023]  Open
9
Vuckovic S, Bahmann H. Nonlocal Functionals Inspired by the Strongly Interacting Limit of DFT: Exact Constraints and Implementation. J Chem Theory Comput 2023;19:6172-6184. [PMID: 37611177 DOI: 10.1021/acs.jctc.3c00437] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
10
Hagg A, Kirschner KN. Open-Source Machine Learning in Computational Chemistry. J Chem Inf Model 2023;63:4505-4532. [PMID: 37466636 PMCID: PMC10430767 DOI: 10.1021/acs.jcim.3c00643] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Indexed: 07/20/2023]
11
Huang B, von Rudorff GF, von Lilienfeld OA. The central role of density functional theory in the AI age. Science 2023;381:170-175. [PMID: 37440654 DOI: 10.1126/science.abn3445] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 05/30/2023] [Indexed: 07/15/2023]
12
Cuierrier E, Roy PO, Wang R, Ernzerhof M. The fourth-order expansion of the exchange hole and neural networks to construct exchange–correlation functionals. J Chem Phys 2022;157:171103. [DOI: 10.1063/5.0122761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]  Open
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