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Paper Citation Record · LEDGER

GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:1809.11165.

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

pith.paper-citation-record.v1
1809.11165 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:55:36.736540Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

539
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b7a173f8-e298-40b6-926e-c3ece20f33c9 · inbound

Deep learning applied to computational mechanics: A comprehensive review, state of the art, and the classics cites this paper.

Deep learning applied to computational mechanics: A comprehensive review, state of the art, and the classics GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

Reference 280

Resolution
verified exact
arxiv_id, observed 2026-05-24T10:24:20.210843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 852377fc-040d-407e-90e6-6a75e9112a7b · inbound

A tutorial on learning from preferences and choices with Gaussian Processes cites this paper.

A tutorial on learning from preferences and choices with Gaussian Processes GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-24T03:28:50.258294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-24T03:26:14.370450Z digest=sha256:11260d676ecf6b2436790c497c66011e12fcf7ac3caef1ee0efbf6b3dd89173d

Observation 110378b0-9fe7-4481-9494-ca6f97a2a48b · inbound

High-Dimensional Bayesian Optimisation with Large-Scale Constraints via Latent Space Gaussian Processes cites this paper.

High-Dimensional Bayesian Optimisation with Large-Scale Constraints via Latent Space Gaussian Processes GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T11:16:41.057309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:16:41.057309Z digest=sha256:52360c9feba093745a5160c6f805f7f9f4ad13b463bdae781f7831c736b43584

Observation ce6c52ab-44b3-4af4-9451-1d220fd0ccc0 · inbound

Gaussian Process Methods for Very Large Astrometric Data Sets cites this paper.

Gaussian Process Methods for Very Large Astrometric Data Sets GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T17:42:14.715011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:42:14.715011Z digest=sha256:4df791046fa02c1c5fbd5124d05e09c6fae20540d056a5c2610dce1b79ca593d

Observation ec88f7d5-d740-4ece-880d-792195ac182a · inbound

Physics-informed automated surface reconstructing via low-energy electron diffraction based on Bayesian optimization cites this paper.

Physics-informed automated surface reconstructing via low-energy electron diffraction based on Bayesian optimization GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-05-10T19:55:44.927130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-10T19:55:09.055264Z digest=sha256:c9aa67d99271c6a6c648f43a7c16f8fdb5e535921e1cafe6e2516a6e716d7d6e

Observation 5e5fdf91-45fd-45ad-b9ce-8ad3ae1e829b · inbound

Accelerated Dopant Screening in Oxide Semiconductors via Multi-Fidelity Contextual Bandits and a Three-Tier DFT Validation Funnel cites this paper.

Accelerated Dopant Screening in Oxide Semiconductors via Multi-Fidelity Contextual Bandits and a Three-Tier DFT Validation Funnel GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:56:03.714212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-10T15:44:35.990005Z digest=sha256:8117c0450fbfd727568e016f90955f1efa704198979ec1cf30b064b00eb9c8af

Observation 5170f1b6-74fb-4b95-b1c2-eef0fec510f5 · inbound

Data-Driven Acceleration of Eccentricity Reduction for Binary Black Hole Simulations cites this paper.

Data-Driven Acceleration of Eccentricity Reduction for Binary Black Hole Simulations GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:11:06.164626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-09T20:32:15.051511Z digest=sha256:17430dfcd2b89ae9471d40da06db74d8968d238b3f7af0988e14db53304b1850

Observation 0b2735b5-49a4-43dc-8b9d-1ac3315f0b8d · inbound

Accelerating integrated modeling with surrogate-based optimization: the MAESTRO workflow cites this paper.

Accelerating integrated modeling with surrogate-based optimization: the MAESTRO workflow GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:05:50.852744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-11T01:02:15.713427Z digest=sha256:24ece757593691ee80d92c58de8e99fa1ec16d0eafd1a2519f4e8574bbbb5791

Observation 6b41b0bb-f252-4432-bed8-e4427b38384e · inbound

Probabilistic Data-Driven Modelling of Astrophysical Transients: The Neural Process Family for Ultrafast and Class-Agnostic Light Curve Reconstruction with NightLANP cites this paper.

Probabilistic Data-Driven Modelling of Astrophysical Transients: The Neural Process Family for Ultrafast and Class-Agnostic Light Curve Reconstruction with NightLANP GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-07-01T16:05:48.813295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-01T16:04:28.087336Z digest=sha256:70c07f9d5e0c8b2e89a783f2e1840c4969fa17b64edc442359c337d08866e8de

Observation 9fa2159c-dc92-48d1-8b87-a5746c5de3fd · inbound

Constrained Bayesian Optimisation with Multiple Information Sources cites this paper.

Constrained Bayesian Optimisation with Multiple Information Sources GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-07-02T15:57:06.276212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-07-02T15:52:24.436940Z digest=sha256:dcf03afaf9cdc3b7601fc9e0a7becd35425d26b977c4c952d7fbde6d233c895b

Observation d73d1261-ebb9-4996-bef4-8d2ae67dacbd · inbound

A Gaussian Process framework for constraining the nuclear equation of state from microscopic calculations with correlated uncertainties cites this paper.

A Gaussian Process framework for constraining the nuclear equation of state from microscopic calculations with correlated uncertainties GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

Reference 148

Resolution
unresolved
no resolver link, observed 2026-08-11T12:55:36.736540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:55:36.736540Z digest=sha256:a07794f61c93b0104614c53fe40b563035aca5ff935dd815b5598d278edbad0f