Cristin-person-ID: 698433
Person

Sigbjørn Løland Bore

  • Stilling:
    Forsker
    ved Hylleraas-senteret ved Universitetet i Oslo

Resultater Resultater

Learning Force Field Parameters from Differentiable Particle-Field Molecular Dynamics.

Carrer, Manuel; Musseli Cezar, Henrique; Bore, Sigbjørn Løland; Ledum, Morten; Cascella, Michele. 2024, Journal of Chemical Information and Computer Sciences. UIOVitenskapelig artikkel

Machine Learned Potential for Organolithium in THF.

Eliasson, Sondre Hilmar Hopen; de Giovanetti, Marinella; Bore, Sigbjørn Løland; Bortoli, Marco; Cascella, Michele; Eisenstein, Odile. 2023, TRAINS Conference . UIOPoster

Machine Learned Potential for Organolithium Compounds in THF. .

Eliasson, Sondre Hilmar Hopen; de Giovanetti, Marinella; Bore, Sigbjørn Løland; Bortoli, Marco; Cascella, Michele. 2023, European Conference on Computational and Theoretical Chemistry. UIOPoster

Realistic phase diagram of water from “first principles” data-driven quantum simulations.

Bore, Sigbjørn Løland; Paesani, Francesco. 2023, Nature Communications. UCSDVitenskapelig artikkel

DeePMD-kit v2: A software package for deep potential models.

Zeng, Jinzhe; Zhang, Duo; Lu, Denghui; Mo, Pinghui; Li, Zeyu; Chen, Yixiao; Rynik, Marián; Huang, Li’ang; Li, Ziyao; Shi, Shaochen mfl.. 2023, Journal of Chemical Physics. TU, UTOKYO, USA, CUitCoNY, UKvB, PU, ECNUS, UCAS, IITPKD, RTSUONJ, STORBRITAN, HU, TQUOB, EPFL, KINA, NUDT, SISdSAdT, UIO, PKU, XUVitenskapelig artikkel
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