{"total":24,"rows":[{"id":"2505.12149","title":"Improving Energy Natural Gradient Descent through Woodbury, Momentum, and Randomization","created":"2025-05-17","cited_by_count":13,"area":null},{"id":"2506.10973","title":"Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning","created":"2025-06-12","cited_by_count":12,"area":null},{"id":"2604.05230","title":"Curvature-Aware Optimization for High-Accuracy Physics-Informed Neural Networks","created":"2026-04-06","cited_by_count":11,"area":null},{"id":"2405.14762","title":"Neural Pfaffians: Solving Many Many-Electron Schr\\\"odinger Equations","created":"2024-05-23","cited_by_count":9,"area":null},{"id":"2504.06087","title":"Accurate Ab-initio Neural-network Solutions to Large-Scale Electronic Structure Problems","created":"2025-04-08","cited_by_count":8,"area":null},{"id":"2507.10835","title":"Functional Neural Wavefunction Optimization","created":"2025-07-14","cited_by_count":3,"area":null},{"id":"2502.00882","title":"Worth Their Weight: Randomized and Regularized Block Kaczmarz Algorithms without Preprocessing","created":"2025-02-02","cited_by_count":2,"area":null},{"id":"2508.21022","title":"A Sketch-and-Project Analysis of Subsampled Natural Gradient Algorithms","created":"2025-08-28","cited_by_count":2,"area":null},{"id":"2511.01671","title":"Spin-Adapted Neural Network Wavefunctions in Real Space","created":"2025-11-03","cited_by_count":2,"area":null},{"id":"2604.15554","title":"Natural gradient descent with momentum","created":"2026-04-16","cited_by_count":2,"area":null},{"id":"2603.14515","title":"Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State","created":"2026-03-15","cited_by_count":1,"area":null},{"id":"2605.00284","title":"A Dirac-Frenkel-Onsager principle: Instantaneous residual minimization with gauge momentum for nonlinear parametrizations of PDE solutions","created":"2026-04-30","cited_by_count":1,"area":null},{"id":"2609.23334","title":"Stochastic Reconfiguration as Statistical Filtering for Overparameterized Neural Quantum States","created":"2026-09-20","cited_by_count":1,"area":null},{"id":"2405.19397","title":"Ground state phases of the two-dimension electron gas with a unified variational approach","created":"2024-05-29","cited_by_count":0,"area":null},{"id":"2409.01978","title":"Application of Langevin Dynamics to Advance the Quantum Natural Gradient Optimization Algorithm","created":"2024-09-03","cited_by_count":0,"area":null},{"id":"2509.12431","title":"Neural-Quantum-States Impurity Solver for Quantum Embedding Problems","created":"2025-09-15","cited_by_count":0,"area":null},{"id":"2512.04663","title":"Fermionic neural Gibbs states","created":"2025-12-04","cited_by_count":0,"area":null},{"id":"2601.10498","title":"PROMA: Projected Microbatch Accumulation for Reference-Free Proximal Policy Updates","created":"2026-01-15","cited_by_count":0,"area":null},{"id":"2602.09093","title":"Predicting magnetism with first-principles AI","created":"2026-02-09","cited_by_count":0,"area":null},{"id":"2606.24769","title":"Dirac-Frenkel dynamics with inertia for nonlinearly parametrized solutions of evolution problems","created":"2026-06-23","cited_by_count":0,"area":null},{"id":"2607.18865","title":"Enhanced Neural Quantum State via Annealed Gradient Descent","created":"2026-07-21","cited_by_count":0,"area":null},{"id":"2607.22004","title":"Energy Manifold Natural Gradient Descent: Riemannian Optimization for Neural PDE Solvers","created":"2026-07-24","cited_by_count":0,"area":null},{"id":"2609.36738","title":"Backpropagated Output Momentum: Relocating Optimizer History from Parameters to Task Space","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.12985","title":"NucleoNet: A Nuclear-Aware Determinant Ansatz for Multi-Geometry Neural Variational Monte Carlo","created":"2026-10-09","cited_by_count":0,"area":null}],"next_cursor":null}