Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:09:25.542897Z
Paper Citation Record · LEDGER
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods
As of 8 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2506.03471.
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 2026-08-07T06:34:17.273281+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
Reference resolution
47 of 47 outbound references displayed
- verified exact1
- verified fuzzy38
- unresolved8
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 747aa79a-9bb4-446a-b849-52bb495ceba9 · outbound
This paper cites Gaussian processes for regression.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Gaussian processes for regression
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:32.186135Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f323ce4f-7cbb-48ee-84d1-42d0d0f35896 · outbound
This paper cites Rasmussen and C.K.I.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Rasmussen and C.K.I
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:31.984578Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation af1da83e-31e1-4c5c-b792-2203bea28b66 · outbound
This paper cites Gaussian processes in machine learning.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Gaussian processes in machine learning
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:09:21.951539Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 22740c97-c8c0-492c-ae69-69dcc082060b · outbound
This paper cites Kernel methods in machine learning.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Kernel methods in machine learning
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:31.821220Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a0f09c00-5678-4db6-ac94-01519c07c84c · outbound
This paper cites A tutorial on gaussian process regression: Modelling, exploring, and exploiting functions.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods A tutorial on gaussian process regression: Modelling, exploring, and exploiting functions
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:31.655992Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9828d835-d35d-43d2-b673-c868800f804c · outbound
This paper cites When gaussian process meets big data: A review of scalable gps.IEEE transactions on neural networks and learning systems, 31(11):4405–4423, 2020.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods When gaussian process meets big data: A review of scalable gps.IEEE transactions on neural networks and learning systems, 31(11):4405–4423, 2020
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:09:22.350555Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e3ee7410-be70-46ab-a38e-51923fb3a036 · outbound
This paper cites Fast gaussian process regression for big data.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Fast gaussian process regression for big data
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:31.498734Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5f39decc-3a56-473b-af7e-b9a1b37356fb · outbound
This paper cites Gaussian Process Behaviour in Wide Deep Neural Networks.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Gaussian Process Behaviour in Wide Deep Neural Networks
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:09:22.595147Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 79a89fde-04d7-4ade-b885-4096d805e2f9 · outbound
This paper cites Deep Convolutional Networks as shallow Gaussian Processes.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Deep Convolutional Networks as shallow Gaussian Processes
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:09:22.699302Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ac39e58e-e7ad-4be6-95c1-6586bf8aa676 · outbound
This paper cites Gaussian processes for time-series modelling.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Gaussian processes for time-series modelling
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:31.340012Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9683bd1d-87b6-41c9-bc1a-952a727f2bdf · outbound
This paper cites Fast and scalable gaussian process modeling with applications to astronomical time series.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Fast and scalable gaussian process modeling with applications to astronomical time series
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:31.179205Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 35d154c0-1b42-4509-8ce2-b130eec71f28 · outbound
This paper cites Time series forecasting with gaussian processes needs priors.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Time series forecasting with gaussian processes needs priors
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:31.061756Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a226133b-ddbe-484b-ac15-5eb4273fa567 · outbound
This paper cites Gaussian process for nonstationary time series prediction.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Gaussian process for nonstationary time series prediction
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:30.973155Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0a75ad53-da2a-4daa-878b-55d2d3ff2abb · outbound
This paper cites Gaussian processes for data-e fficient learning in robotics and control.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Gaussian processes for data-e fficient learning in robotics and control
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:30.899036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1933a9b8-43b8-4237-990f-e098c5db5235 · outbound
This paper cites Gaussian processes in reinforcement learning.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Gaussian processes in reinforcement learning
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:30.783522Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 45106b38-beb8-4b2c-8155-e41a0d9a775d · outbound
This paper cites A gaussian process upsampling model for improvements in optical character recognition.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods A gaussian process upsampling model for improvements in optical character recognition
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:30.668328Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4ee22696-c490-42b0-9134-73dace13bfc3 · outbound
This paper cites Individualized gaussian process-based prediction and detection of local and global gray matter abnormalities in elderly subjects.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Individualized gaussian process-based prediction and detection of local and global gray matter abnormalities in elderly subjects
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:30.560329Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 16c8f26b-6de5-403e-bc3b-1b0c81e6b416 · outbound
This paper cites Gaussian process regression stochastic volatility model for financial time series.IEEE Journal of Selected Topics in Signal Processing, 10(6):1015–1028, 2016.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Gaussian process regression stochastic volatility model for financial time series.IEEE Journal of Selected Topics in Signal Processing, 10(6):1015–1028, 2016
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:30.464918Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f1ddb03a-b1ac-4931-a9dd-cab6bf99c71c · outbound
This paper cites Price forecasts of ten steel products using gaussian process regressions.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Price forecasts of ten steel products using gaussian process regressions
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:30.380072Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3750964f-4ac7-42d2-a7df-a1cce6aed796 · outbound
This paper cites Prediction with gaussian processes: From linear regression to linear prediction and beyond.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Prediction with gaussian processes: From linear regression to linear prediction and beyond
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:30.307855Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d31efe92-8303-4d49-82d5-dd23d2fb5039 · outbound
This paper cites New high-order methods using gaussian processes for computational fluid dynamics simulations.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods New high-order methods using gaussian processes for computational fluid dynamics simulations
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:30.212186Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c1d6a008-ecd8-4361-8eb9-37455a01b238 · outbound
This paper cites E fficient implementation of essentially non-oscillatory shock-capturing schemes, II.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods E fficient implementation of essentially non-oscillatory shock-capturing schemes, II
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:30.125354Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 13a08544-d171-47b3-92c3-f45a3fd581ca · outbound
This paper cites A new class of high-order methods for fluid dynamics simulations using gaussian process modeling: One-dimensional case.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods A new class of high-order methods for fluid dynamics simulations using gaussian process modeling: One-dimensional case
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:30.053321Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation baaa34b7-d49a-40f5-bc4f-48ecc076f3b3 · outbound
This paper cites E fficient implementation of weighted ENO schemes.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods E fficient implementation of weighted ENO schemes
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:29.983484Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 14192db5-a189-401f-a306-335804ed4e71 · outbound
This paper cites A variable high-order shock-capturing finite di fference method with GP-WENO.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods A variable high-order shock-capturing finite di fference method with GP-WENO
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:29.910570Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 20f27fb5-b143-4416-8453-1838e5738436 · outbound
This paper cites High-order genuinely multidimensional finite volume methods via kernel-based weno.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods High-order genuinely multidimensional finite volume methods via kernel-based weno
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:29.846699Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a4b94040-1696-4c48-b5a5-52bbaa94b574 · outbound
This paper cites Kfvm-weno: A high-order accurate kernel-based finite volume method for compressible hydrodynamics.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Kfvm-weno: A high-order accurate kernel-based finite volume method for compressible hydrodynamics
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:29.789622Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e14b105e-aa25-4a2b-924f-f7883a30b904 · outbound
This paper cites Balsara, Sudip Garain, and Chi Wang Shu.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Balsara, Sudip Garain, and Chi Wang Shu
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:29.753416Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a0f00a96-b897-4257-ab94-0386941986ae · outbound
This paper cites Essentially non-oscillatory and weighted essentially non-oscillatory schemes for hyperbolic conservation laws.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Essentially non-oscillatory and weighted essentially non-oscillatory schemes for hyperbolic conservation laws
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:29.558216Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ecceb3b0-c2c0-4d35-9b6e-393765acec75 · outbound
This paper cites A survey of the isentropic Euler vortex problem using high-order methods.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods A survey of the isentropic Euler vortex problem using high-order methods
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:29.337116Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 25c4a13d-96a0-4215-ba21-6628e11dad2d · outbound
This paper cites A high-order finite volume method for systems of conservation laws—multi-dimensional optimal order detection (MOOD).
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods A high-order finite volume method for systems of conservation laws—multi-dimensional optimal order detection (MOOD)
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:29.059897Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 513fe3ae-d5f8-48f4-a174-e9a5f834d5ad · outbound
This paper cites Improved detection criteria for the multi-dimensional optimal order detection (MOOD) on unstructured meshes with very high-order polynomials.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Improved detection criteria for the multi-dimensional optimal order detection (MOOD) on unstructured meshes with very high-order polynomials
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:28.845346Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 32acc0c6-e4f8-4f83-b6c5-c03d32859fe5 · outbound
This paper cites The multidimensional optimal order detection method in the three-dimensional case: very high-order finite volume method for hyperbolic systems.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods The multidimensional optimal order detection method in the three-dimensional case: very high-order finite volume method for hyperbolic systems
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:28.596706Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 2a07e780-477f-4011-b227-0758e0ddf41d · outbound
This paper cites La m´ ethode MOOD Multi-dimensional Optimal Order Detection: la premi` ere approche a posteriori aux m´ ethodes volumes finis d’ordre tr` es ´ elev´ e.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods La m´ ethode MOOD Multi-dimensional Optimal Order Detection: la premi` ere approche a posteriori aux m´ ethodes volumes finis d’ordre tr` es ´ elev´ e
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:28.360095Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation bfb617e8-d11a-4ac4-9746-9cc3a5ce5f6b · outbound
This paper cites A priori neural networks versus a posteriori mood loop: A high accurate 1d fv scheme testing bed.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods A priori neural networks versus a posteriori mood loop: A high accurate 1d fv scheme testing bed
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:28.115531Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a551be76-f4b4-4e80-ae35-b4aa1f492d8b · outbound
This paper cites Gp-mood: a positivity-preserving high-order finite volume method for hyperbolic conservation laws.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Gp-mood: a positivity-preserving high-order finite volume method for hyperbolic conservation laws
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:27.755836Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d9cda477-87a3-4d93-a988-c3fff9f60aa5 · outbound
This paper cites Gp-mood: A positivity-preserving high-order finite volume method for hyperbolic conservation laws.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Gp-mood: A positivity-preserving high-order finite volume method for hyperbolic conservation laws
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:27.397283Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e6a30949-d232-4d46-8aa7-c41b651e6ecb · outbound
This paper cites An Application of Gaussian Process Modeling for High-order Accurate Adaptive Mesh Refinement Prolongation.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods An Application of Gaussian Process Modeling for High-order Accurate Adaptive Mesh Refinement Prolongation
Reference 38
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T11:09:25.684067Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation fc3d67ec-349e-4dba-9f10-f48d2839bbea · outbound
This paper cites A high-order finite-volume method for conservation laws on locally refined grids.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods A high-order finite-volume method for conservation laws on locally refined grids
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:27.036157Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4b61d77a-1137-44a7-9e78-2d59fc08dcd2 · outbound
This paper cites Improved accuracy of high-order WENO finite volume methods on Cartesian grids.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Improved accuracy of high-order WENO finite volume methods on Cartesian grids
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:26.801850Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 28a06bb8-fd32-4975-b3de-6af14b28a2d4 · outbound
This paper cites an unresolved cited work.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Unresolved cited work
Reference 41
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:09:26.550382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1322b4ff-107e-407a-900b-39a03308f8a6 · outbound
This paper cites Interpolation of spatial data: some theory for kriging.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Interpolation of spatial data: some theory for kriging
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:09:25.219138Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2ede1597-998f-4a0c-adbc-32a05941160f · outbound
This paper cites Kernel-based approximation methods using Matlab, volume 19.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Kernel-based approximation methods using Matlab, volume 19
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:26.399981Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b0b24fb7-c1cf-4e7e-ae0e-70a3f20309ed · outbound
This paper cites an unresolved cited work.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Unresolved cited work
Reference 44
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:09:26.248773Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 8065d170-6f9e-433a-ac43-9b6dab266137 · outbound
This paper cites an unresolved cited work.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Unresolved cited work
Reference 45
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:09:26.123915Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 83fd378e-577f-4919-889d-27784bea5668 · outbound
This paper cites Le, Alex J.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Le, Alex J
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:25.979397Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0da546fe-1eff-46ee-b560-5701e673f843 · outbound
This paper cites Most likely heteroscedastic gaussian process regression.
GP-Recipe: Gaussian Process approximation to linear operations in numerical methods Most likely heteroscedastic gaussian process regression
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:09:25.858471Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Pith citing papers
No inbound Pith citation observations are available.