Machine Learning
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Results for: Machine Learning
- Voss, Johannes. “Machine Learning for Accuracy in Density Functional Approximations”, J. Comput. Chem., 45 (April 26, 2024): 1829-45. https://doi.org/10.1002/jcc.27366.
- Deo, Shyam, Melissa Kreider, Gaurav Kamat, McKenzie Hubert, José Zamora Zeledón, Lingze Wei, Jesse Matthews, Nathaniel Keyes, Ishaan Singh, Thomas Jaramillo, Frank Abild-Pedersen, Michaela Burke Stevens, Kirsten Winther, and Johannes Voss. “Interpretable Machine Learning Models for Practical Antimonate Electrocatalyst Performance”, ChemPhysChem. https://doi.org/10.1002/cphc.202400010.
- Trepte, Kai, and Johannes Voss. “Data-Driven and Constrained Optimization of Semi-Local Exchange and Nonlocal Correlation Functionals for Materials and Surface Chemistry”, J. Comput. Chem., 43 (2022): 1104. https://doi.org/10.1002/jcc.26872.
- Voss, Johannes. “Hubbard-Corrected Oxide Formation Enthalpies Without Adjustable Parameters”, J. Phys. Commun., 6 (2022): 035009. https://doi.org/10.1088/2399-6528/ac6069.
- Brown, Kristopher, Yasheng Maimaiti, Kai Trepte, Thomas Bligaard, and Johannes Voss. “MCML: Combining Physical Constraints With Experimental Data for a Multi-Purpose Meta-Generalized Gradient Approximation”, J. Comput. Chem., 42 (2021): 2004. https://doi.org/10.1002/jcc.26732.
- Lundgaard, Keld, Jess Wellendorff, Johannes Voss, Karsten Jacobsen, and Thomas Bligaard. “MBEEF-VdW: Robust Fitting of Error Estimation Density Functionals”, Phys. Rev. B, 93 (2016): 235162. https://doi.org/10.1103/PhysRevB.93.235162.