Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Learning in latent spaces improves the predictive accuracy of deep neural operators
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2304.07599.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T06:01:41.865730Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T08:57:47.599533Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 659949db-4bc1-4957-bac7-f03b38513742 · inbound
Neural Operators for Forward and Inverse Potential-Density Mappings in Classical Density Functional Theory cites this paper.
Neural Operators for Forward and Inverse Potential-Density Mappings in Classical Density Functional Theory Learning in latent spaces improves the predictive accuracy of deep neural operators
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T06:01:41.865730Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3022987c-8eaf-4e87-b15a-cfd4161f6832 · inbound
Vector-Valued Reproducing Kernel Banach Spaces for Neural Networks and Operators cites this paper.
Vector-Valued Reproducing Kernel Banach Spaces for Neural Networks and Operators Learning in latent spaces improves the predictive accuracy of deep neural operators
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T13:43:13.284569Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9a1776e7-f2a6-4d3b-9b38-5b8e8cc81e6f · inbound
$\phi-$DeepONet: A Discontinuity Capturing Neural Operator cites this paper.
$\phi-$DeepONet: A Discontinuity Capturing Neural Operator Learning in latent spaces improves the predictive accuracy of deep neural operators
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T05:46:13.489688Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6ba51f86-110b-4fe3-881f-590260658861 · inbound
Spectrally Regularized Latent Flow Matching for Turbulence Generation cites this paper.
Spectrally Regularized Latent Flow Matching for Turbulence Generation Learning in latent spaces improves the predictive accuracy of deep neural operators
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T08:57:47.601272Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b6acbb87-fd2c-4ed2-9f8f-3d93ccac82be · inbound
Structure-preserving variational neural fields: Uncertainty-quantified reduced-order modeling of nonlinear conservation laws cites this paper.
Structure-preserving variational neural fields: Uncertainty-quantified reduced-order modeling of nonlinear conservation laws Learning in latent spaces improves the predictive accuracy of deep neural operators
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T08:02:00.306457Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.