Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T08:36:46.196757Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2601.17090.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T08:36:46.196757Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
16 of 16 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 565f3a61-d562-4ae2-adec-8d8ab73463eb · outbound
SFO: Learning PDE Operators via Spectral Filtering Spectral State Space Models
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 31c190a4-5047-4773-a91d-09fb29011e49 · outbound
SFO: Learning PDE Operators via Spectral Filtering I., Nguyen, W., Devre, Y ., Dogariu, E., Majumdar, A., and Hazan, E
Reference 9
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d30f6c03-e1a2-4dd6-8f0d-1c8408f79db4 · outbound
SFO: Learning PDE Operators via Spectral Filtering Deep Parallel Spectral Neural Operators for Solving Partial Differential Equations with Enhanced Low-Frequency Learning Capability
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fc657ab7-c1da-4190-a12d-e8849a3b2436 · outbound
SFO: Learning PDE Operators via Spectral Filtering Koopman neural operator as a mesh-free solver of non-linear partial differential equations
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ba2a169b-786b-47bb-9fa2-970822e9901d · outbound
SFO: Learning PDE Operators via Spectral Filtering Analysis of learned Hilbert coefficients
Reference 12
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 78454e04-c7bb-481b-ab6b-522546dddb63 · outbound
SFO: Learning PDE Operators via Spectral Filtering On a finite discretized grid, FFT corresponds to circular convolution and thus implicitly assumes a periodic extension of the domain
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 61a27cfc-bc0c-400e-ac24-e1c4f8931f66 · outbound
SFO: Learning PDE Operators via Spectral Filtering Finally, we obtain G[t] =Udiag(g 1[t],
Reference 14
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b43b219f-a012-4c64-bc65-c4d4331ec9dc · outbound
SFO: Learning PDE Operators via Spectral Filtering Moreover, the Hankel spectrum decays exponentially (see Chapter 11 of (Hazan & Singh, 2022)), yielding the stated logarithmic mode complexity
Reference 15
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3387d5ca-66f5-4e47-8dea-cef9e8a2255e · outbound
SFO: Learning PDE Operators via Spectral Filtering 16 SFO: Learning PDE Solution Operators via Hilbert Spectral Modes We can now prove Theorem G.1 as a simple consequence of the proceeding two lemmas: Proof of Theorem G.1
Reference 16
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6dfa338-dbc0-4756-b005-f372eb49ec50 · outbound
SFO: Learning PDE Operators via Spectral Filtering Universal Learning of Nonlinear Dynamics
Reference 1984
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 83266164-51eb-4469-8bd6-f49d993c7824 · outbound
SFO: Learning PDE Operators via Spectral Filtering Introduction to Online Control
Reference 2000
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 92380c23-6b20-42be-b172-bb5084b8d1bb · outbound
SFO: Learning PDE Operators via Spectral Filtering Unresolved cited work
Reference 2017
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 56cd31a6-6d53-4667-aab8-f7fd4cf48d02 · outbound
SFO: Learning PDE Operators via Spectral Filtering Neural Operator: Graph Kernel Network for Partial Differential Equations
Reference 2021
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f1c3ac8d-025a-4211-ad60-fa8049b0c760 · outbound
SFO: Learning PDE Operators via Spectral Filtering LNO: Laplace Neural Operator for Solving Differential Equations
Reference 2022
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 669e909e-09df-434f-962c-89d21a9f7bf1 · outbound
SFO: Learning PDE Operators via Spectral Filtering Galerkin transformer
Reference 2023
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c30e83ed-9ada-4700-bcca-05568278658f · outbound
SFO: Learning PDE Operators via Spectral Filtering Operator Learning Enhanced Physics-informed Neural Networks for Solving Partial Differential Equations Characterized by Sharp Solutions
Reference 2024
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.