Articlenpj computational materials2025
Machine learning Hubbard parameters with equivariant neural networks.
Article in npj computational materials, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Bayesian Modeling of Polarizable Water: Lessons for Force Field Development.Journal of chemical theory and computation · 2026Article
- Bayesian Optimization of Catalysis with In-Context Learning.ACS central science · 2026Article
- Many-Body Benchmark of Electronic Charge and Spin Densities for LiJournal of chemical theory and computation · 2026Article
- Getting the Manifold Right: The Crucial Role of Orbital Resolution in DFT+Journal of chemical theory and computation · 2026Article
- Comparing Hubbard parameters from linear-response theory and a Hartree-Fock-based approach.npj computational materials · 2026Article
- TBHubbard: tight-binding and extended Hubbard model dataset for metal-organic frameworks.Scientific data · 2025Article
- First-principles Hubbard parameters with automated and reproducible workflows.npj computational materials · 2025Article
- Magnons from time-dependent density-functional perturbation theory and nonempirical Hubbard functionals.npj computational materials · 2025Article
- Predicting electronic screening for fast Koopmans spectral functional calculations.npj computational materials · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Density-functional theory with extended Hubbard functionals (DFT +
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.