Alfred Nordman
Assistent med doktoranduppgifter vid Institutionen för cell- och molekylärbiologi; Beräkningsbiologi och bioinformatik
- E-post:
- alfred.nordman@icm.uu.se
- Besöksadress:
- Husargatan 3
752 37 Uppsala - Postadress:
- Box 596
751 24 UPPSALA
Publikationer
Senaste publikationer
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Parameters, Potentials and Probabilistic Methods in Molecular Modeling
2026
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Bayesian three-point water models
Ingår i npj Computational Materials, 2025
- DOI för Bayesian three-point water models
- Ladda ner fulltext (pdf) av Bayesian three-point water models
-
Evolutionary machine learning of physics-based force fields in high-dimensional parameter-space
Ingår i Digital Discovery, s. 1925-1935, 2025
- DOI för Evolutionary machine learning of physics-based force fields in high-dimensional parameter-space
- Ladda ner fulltext (pdf) av Evolutionary machine learning of physics-based force fields in high-dimensional parameter-space
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An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation
Ingår i Journal of Chemical Information and Modeling, s. 412-431, 2023
- DOI för An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation
- Ladda ner fulltext (pdf) av An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation
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Theoretical Infrared Spectra: Quantitative Similarity Measures and Force Fields
Ingår i Journal of Chemical Theory and Computation, s. 3307-3315, 2020
- DOI för Theoretical Infrared Spectra: Quantitative Similarity Measures and Force Fields
- Ladda ner fulltext (pdf) av Theoretical Infrared Spectra: Quantitative Similarity Measures and Force Fields
Alla publikationer
Artiklar i tidskrift
-
Bayesian three-point water models
Ingår i npj Computational Materials, 2025
- DOI för Bayesian three-point water models
- Ladda ner fulltext (pdf) av Bayesian three-point water models
-
Evolutionary machine learning of physics-based force fields in high-dimensional parameter-space
Ingår i Digital Discovery, s. 1925-1935, 2025
- DOI för Evolutionary machine learning of physics-based force fields in high-dimensional parameter-space
- Ladda ner fulltext (pdf) av Evolutionary machine learning of physics-based force fields in high-dimensional parameter-space
-
Theoretical Infrared Spectra: Quantitative Similarity Measures and Force Fields
Ingår i Journal of Chemical Theory and Computation, s. 3307-3315, 2020
- DOI för Theoretical Infrared Spectra: Quantitative Similarity Measures and Force Fields
- Ladda ner fulltext (pdf) av Theoretical Infrared Spectra: Quantitative Similarity Measures and Force Fields
Artiklar, forskningsöversikt
-
An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation
Ingår i Journal of Chemical Information and Modeling, s. 412-431, 2023
- DOI för An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation
- Ladda ner fulltext (pdf) av An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation