A graph neural network trained on H4 and H6 predicts optimized orbitals for larger unseen H8-H12 systems with O(10-100) milli-Hartree energy errors and provides effective warm-starts for VQE optimization.
Robust estimation of a location parameter
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
method 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
method 1polarities
use method 1representative citing papers
The paper overviews attention-based learning methods for spectrum cartography in LEO satellite networks to enable adaptive fusion of heterogeneous measurements for inference and resource allocation.
citing papers explorer
-
A Transferable Machine Learning Approach to Predict Optimized Orbitals for Electronic Structure Problems
A graph neural network trained on H4 and H6 predicts optimized orbitals for larger unseen H8-H12 systems with O(10-100) milli-Hartree energy errors and provides effective warm-starts for VQE optimization.
-
Learning-Based Spectrum Cartography in Low Earth Orbit Satellite Networks: An Overview
The paper overviews attention-based learning methods for spectrum cartography in LEO satellite networks to enable adaptive fusion of heterogeneous measurements for inference and resource allocation.