Paper Citation Record · LEDGER

Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States

As of 11 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2606.07825.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2606.07825 v1

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Outbound references

Observation 9ea465a3-45dd-472e-ad89-56637dec3568 · outbound

This paper cites On the momentum term in gradient descent learning algorithms.Neu- ral Networks12, 145–151 (1999).

Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States On the momentum term in gradient descent learning algorithms.Neu- ral Networks12, 145–151 (1999)

Reference 1

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Unresolved cited work

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States & Grosse, R

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States & Singer, Y

Reference 4

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Unresolved cited work

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Science , author =

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This paper cites A., Mathur, S., Salabert, D., Ballot, J., R´egulo, C., Metcalfe, T.

Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States A., Mathur, S., Salabert, D., Ballot, J., R´egulo, C., Metcalfe, T

Reference 7

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Unresolved cited work

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This paper cites and Melko, Roger G.

Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States and Melko, Roger G

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This paper cites Schuyler and Wiersema, Roeland and Hibat-Allah, Mohamed and Carrasquilla, Juan and Melko, Roger G.

Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Schuyler and Wiersema, Roeland and Hibat-Allah, Mohamed and Carrasquilla, Juan and Melko, Roger G

Reference 10

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States 2024 , title =

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States 2023 , title =

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States & Heyl, M

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States & Carleo, G

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States & Holzmann, M

Reference 15

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This paper cites S., Matthews, A.

Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States S., Matthews, A

Reference 16

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Nature Chemistry , author =

Reference 17

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This paper cites An ab initio foundation model of wavefunctions that accurately describes chemical bond breaking.

Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States An ab initio foundation model of wavefunctions that accurately describes chemical bond breaking

Reference 18

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States A Self-Attention Ansatz for Ab-initio Quantum Chemistry

Reference 19

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States & Grohs, P

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States URL https://doi.org/10.1038/s42256-024-00794-x

Reference 21

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States R., Carleo, G., Georges, A

Reference 22

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This paper cites Communications Physics7, 148 (2024).

Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Communications Physics7, 148 (2024)

Reference 23

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States T.et al.Neural wave functions for superfluids.Phys

Reference 24

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States & Spencer, J

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This paper cites Physical Review Letters 85(10), 2200–2203 (2000).

Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Physical Review Letters 85(10), 2200–2203 (2000)

Reference 26

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States L., Bardone, L., Becca, F

Reference 27

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States (eds Oh, A

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States & Lin, L

Reference 30

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Unresolved cited work

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States An Analysis of First- and Quasi-Second-Order Optimization Algorithms in Variational Monte Carlo

Reference 32

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Neural Scaling Laws Surpass Chemical Accuracy for the Many-Electron Schr\"odinger Equation

Reference 33

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This paper cites Solving the Hubbard model with Neural Quantum States.

Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Solving the Hubbard model with Neural Quantum States

Reference 34

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States & Zeinhofer, M

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Jiang, H

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States N., Motrunich, O

Reference 38

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States & Becca, F

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States & Farnell, D

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States and Izaac, J

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States & Umrigar, C

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States URL http://github.com/jax-ml/jax

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States arXiv preprint arXiv:2403.19234 (2024)

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Regularized dynamical parametric approximation of stiff evolution problems

Reference 46

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Absil, R

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States & Sepulchre, R.Optimization algorithms on matrix manifolds(Princeton University Press, 2008)

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States Codebases7 (2022)

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Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States URL https://www.sciencedirect.com/ science/article/pii/S2352711019300974

Reference 50

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