Pith. sign in

Paper Citation Record · LEDGER

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression

As of 18 August 2026, this Paper Citation Record lists 100 of 300 outbound references and 0 inbound Pith citation observations for arXiv:2608.11917.

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

pith.paper-citation-record.v1
2608.11917 v1

Coverage vector

measured 100 of 300 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:30:59.377062Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

100 of 300 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved97
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b3e47465-2251-4326-8789-475e3e8086fd · outbound

This paper cites an unresolved cited work.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.008004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.008004Z digest=sha256:a5947aa3ff3ec424085c072a07e4f49de29a4621a290787e5c5838d6f53b593d

Observation 9c8ed89e-b6ed-46e1-93a8-875e45f173cf · outbound

This paper cites and Shipp, Stewart and Friston, Karl J.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Shipp, Stewart and Friston, Karl J

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.012111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.012111Z digest=sha256:925f2696f402bebfe97cde317d80a151569fafb452ada7ac6c8ebc0428d28e46

Observation 7560b989-ca10-47b5-a10d-dc6f067ee2a9 · outbound

This paper cites and Murphy, Kevin , year = 2018, month = jul, pages =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Murphy, Kevin , year = 2018, month = jul, pages =

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.016272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.016272Z digest=sha256:c7e99e5d0e78fdd419689f49b8a4c9aa6750a9e827e823e3a13a041aadd3b88f

Observation 9c4a911c-f08d-45eb-8077-b44ee96b142d · outbound

This paper cites Computationally Efficient Convolved Multiple Output.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Computationally Efficient Convolved Multiple Output

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.020456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.020456Z digest=sha256:06a22301839ca4c643cebb9ba37e8d93050561099c9e898a11cfc0186b081aab

Observation 036aae26-4274-4951-8419-979cda051432 · outbound

This paper cites Foundations and Trends in Machine Learning , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Foundations and Trends in Machine Learning , volume =

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.024745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.024745Z digest=sha256:bd6c49f117fba6b97d647a6149fa739831f263a92f72b1cc17c62d6fce5ee9e7

Observation 3d5eaff5-477f-4dd8-b03e-8f267d4e0281 · outbound

This paper cites , year = 2012, month = jun, pages =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression , year = 2012, month = jun, pages =

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.028701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.028701Z digest=sha256:f5980acf56ad08a6207a84fd630a2229a8482b94c94b099bccb1f6b49199da85

Observation b19c64fd-95c9-4968-9746-fe60deb84d70 · outbound

This paper cites an unresolved cited work.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.033137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.033137Z digest=sha256:ef6b2e369b614baea4f53c1224ca94116bd93f8cd0b120d9022fcdb9ace41097

Observation a63d485d-eabf-4d2f-bb80-e7211243cf4d · outbound

This paper cites Biosystems , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Biosystems , volume =

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.037308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.037308Z digest=sha256:2ce58b8a23f28ce9119414761abdd47c65efd39120568cb3b48c9a49e490dbf5

Observation b7272169-663d-4751-8bb1-24c7ad8f8e00 · outbound

This paper cites Declarative.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Declarative

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.041287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.041287Z digest=sha256:25261a1c567e3a7ca5be4134f83bd96ca557529eb74a449729603f30143f6c43

Observation 78d55edb-b182-4eb4-85c0-0c0311b1352b · outbound

This paper cites doi:10.1007/978-3-319-20451-2 , urldate =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression doi:10.1007/978-3-319-20451-2 , urldate =

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.045092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.045092Z digest=sha256:9769a97dbb6e416d3af8fa52ed0391d690a294edf002176115b658fe74b93116

Observation 83517fe4-aed6-43ae-b2c7-3ec2a083cd67 · outbound

This paper cites and Nouri, Ali and Wingate, David , year = 2009, month = jun, series =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Nouri, Ali and Wingate, David , year = 2009, month = jun, series =

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.049023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.049023Z digest=sha256:0b4892a8f2b025a886dfdbfee5c63ff3f019e213ace3f2bbec072771b85b8ecb

Observation 8528384c-49f7-4b5c-8fb4-0a3aeeebb52b · outbound

This paper cites A Bayesian Sampling Approach to Exploration in Reinforcement Learning.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression A Bayesian Sampling Approach to Exploration in Reinforcement Learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.053488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.053488Z digest=sha256:e01f3258dabe7486e3552c9825d9f723a0baaa17a4e9260acdb03e6ba40c676f

Observation b940aa56-2f6e-42c9-ac1d-93fe9daa7c1c · outbound

This paper cites Planning by Probabilistic Inference , booktitle =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Planning by Probabilistic Inference , booktitle =

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.057893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.057893Z digest=sha256:fd69b122f7a791d9e35782a3275024c9dca43a9bff05c62890c9f81809b03219

Observation 5c494bc5-26b3-4d1f-8675-031bcdd80416 · outbound

This paper cites Reinforcement.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Reinforcement

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.061793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.061793Z digest=sha256:04fcf8afa6af2ddd08ec2b0e7586bf308f3b3d4053f13df97133dafc69fc85e3

Observation 865264fb-d91e-4373-b84e-77c34937208c · outbound

This paper cites Reactive Message Passing for Scalable Bayesian Inference.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Reactive Message Passing for Scalable Bayesian Inference

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.065717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.065717Z digest=sha256:f2915042ca1bcada0420106d4470a59276ed8b00f645c38cda0b5aa0b9e5416b

Observation 40cf8844-5be1-4eaa-9a11-a5c75379987f · outbound

This paper cites Reactive.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Reactive

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.070492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.070492Z digest=sha256:cefeee58f8b29d9f4b836fec07f3ba3d3a342ec7d52559317c532a3a6daa6f50

Observation 7f99083a-a3d1-458e-84a4-0a43771e0d31 · outbound

This paper cites Software Impacts , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Software Impacts , volume =

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.074444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.074444Z digest=sha256:2380d1fd7a6e6bd712196c28f96e7cdfb254b367ae8e0a31ede16878e410f199

Observation 71c159f8-1fd1-42d4-a318-42558de95e8c · outbound

This paper cites doi:10.21105/joss.05161 , urldate =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression doi:10.21105/joss.05161 , urldate =

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.078316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.078316Z digest=sha256:4cce12dae6dec61a13c1a38f21092b22a7327b2df873dcceecf984c2d44ec8ab

Observation 268a2679-f2a5-4e65-8c68-70bcd0a680ba · outbound

This paper cites ACM Computing Surveys (CSUR) , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression ACM Computing Surveys (CSUR) , volume =

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.082259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.082259Z digest=sha256:8552dea4a663bfb7ca532a479bb503aa99b39b59892e46252d7d9de9d16641be

Observation fc7be383-e69e-42a3-af00-8e466e167d2a · outbound

This paper cites and Simpson, Daniel and Rue, H.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Simpson, Daniel and Rue, H

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.086280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.086280Z digest=sha256:fecd3f171d09ac565fa72e0e922c0cdc42e0e038f208a0ba72875ba3ff82566c

Observation b04b5ede-025b-4f11-bf92-71a225347a76 · outbound

This paper cites and Daulton, Samuel and Letham, Benjamin and Wilson, Andrew Gordon and Bakshy, Eytan , year = 2020, month = dec, series =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Daulton, Samuel and Letham, Benjamin and Wilson, Andrew Gordon and Bakshy, Eytan , year = 2020, month = dec, series =

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.090230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.090230Z digest=sha256:88fae2df721cb41b13da3c6e7f61f37624e6a75ab2febe8324893d3f815867f6

Observation 1c20f604-4e13-426a-a493-671228c0b726 · outbound

This paper cites Kalman filters as the steady-state solution of gradient descent on variational free energy.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Kalman filters as the steady-state solution of gradient descent on variational free energy

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.093789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.093789Z digest=sha256:bfa66eaa88ad51c2a35833a7dd14c68cefe938203ac46235638ec467346cb08e

Observation 9e365257-f5be-45ab-9d34-bedcf452106d · outbound

This paper cites Reactive Probabilistic Programming , booktitle =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Reactive Probabilistic Programming , booktitle =

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.098131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.098131Z digest=sha256:e6986d59b801b2d84b81c1c0d638f2d96d22881c05c468029f0daa284d77b9d5

Observation 8d2f66be-4ad1-4300-b0f9-266479a55c13 · outbound

This paper cites doi:10.1098/rstl.1763.0053 , urldate =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression doi:10.1098/rstl.1763.0053 , urldate =

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.101932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.101932Z digest=sha256:fa723b56a66bd87b3c42de5731393ab4e5a4dac8078f2cba30a394951e8b88ea

Observation ed70d514-fa1b-4407-8431-5168beff987d · outbound

This paper cites Dynamic Markov Blanket Detection for Macroscopic Physics Discovery.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Dynamic Markov Blanket Detection for Macroscopic Physics Discovery

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.105620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.105620Z digest=sha256:8888612b527be1db50a8cd8a98fdafb94a8126cd92186f4f72fc971dd69e14dd

Observation bc3bef7e-8795-4d13-bf94-c4b1f0a69203 · outbound

This paper cites Unifying.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unifying

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.109705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.109705Z digest=sha256:101b75f68428b3569004155415fbc08f70d02113ceda50fe57215890398924f2

Observation 6a18cb03-6df9-4fed-a6ac-e92a111df89d · outbound

This paper cites an unresolved cited work.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.112809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.112809Z digest=sha256:fe15875e98fdcb3ddd69f907303236f5427d8656e2de1b24783e751719601546

Observation 49969cd3-15b6-4000-8e83-97ed8ed0363d · outbound

This paper cites Bulletin of the American Mathematical Society , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Bulletin of the American Mathematical Society , volume =

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.116178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.116178Z digest=sha256:465b39fb51ce81f432a4c6d159b1628620df71d0ddffd0f49f6fc8737fecb392

Observation 591f6cbb-7c5f-4810-973c-e9873c70670e · outbound

This paper cites Robustness in Identification and Control , author =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Robustness in Identification and Control , author =

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.119238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.119238Z digest=sha256:61fa68988e1badb6e2b63648364a6e77b31c09fe3b8545da8ac3d37b5ff24170

Observation e4542116-b5bf-4808-bc6b-f4cecd96ed99 · outbound

This paper cites an unresolved cited work.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.122256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.122256Z digest=sha256:9c5cbb430c7fb3cd481cc12222e2f9c56ed314173f4c00ac57505b97122f6d4e

Observation 8062d43d-1a01-44b9-a787-801e25b25dbb · outbound

This paper cites Dynamic Programming and Optimal Control:.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Dynamic Programming and Optimal Control:

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.125697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.125697Z digest=sha256:a548eb9e86dbf86248c744727e58396700199676c7503dceea22f9d4c7962bf8

Observation 62121247-a3e9-4471-ae35-2b6bc6c6e7eb · outbound

This paper cites Julia: A Fresh Approach to Numerical Computing.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Julia: A Fresh Approach to Numerical Computing

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.128966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.128966Z digest=sha256:aef6116406cb30e7befa87dd01d0c9ad2ad9fe67b087bd1629f5ad9352325447

Observation 6f3bf694-1e6a-49f8-8b11-73d413c3507e · outbound

This paper cites an unresolved cited work.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.132342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.132342Z digest=sha256:2d9a601ce2a703e94c103bd219aaadb2d2fe257e6342c757ac7b5e8dfcd0f9ec

Observation 6d792e49-0c69-4683-84a1-2a7720b0ae13 · outbound

This paper cites an unresolved cited work.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.135511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.135511Z digest=sha256:84d67f425d636033233d1b85b418babea8d78cf6c694639cedb635d524c450fe

Observation e3513341-d921-4be5-8f21-d64171efd52d · outbound

This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.139108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.139108Z digest=sha256:737639451f6546805f388444ff16a3354943de0c33a2af71d916f922a867c8e5

Observation 39e64e3f-16c6-4cbb-aac3-8160c4dec502 · outbound

This paper cites , year = 2011, month = dec, journal =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression , year = 2011, month = dec, journal =

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.143579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.143579Z digest=sha256:bd23e4a7f37669198db7226d8d8dfe7620f03c2841d462266b30bc36a48c92e7

Observation 49291056-c72c-4c1b-8a85-5470e138a974 · outbound

This paper cites and Jordan, Michael I.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Jordan, Michael I

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.147279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.147279Z digest=sha256:91973e889168a6c657750674fb49a9d15986ad92af277852fa47642c28e4d2ec

Observation a45b13f4-6f03-4cb7-978b-ef5e492bbef8 · outbound

This paper cites and Kucukelbir, Alp and McAuliffe, Jon D.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Kucukelbir, Alp and McAuliffe, Jon D

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.151027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.151027Z digest=sha256:ca7f0a50e7b2a963e191cdd1f5c879b39a1569ab14781f9dd581093585c4ecda

Observation 266cc1a7-403d-4055-b88b-9736c40570e0 · outbound

This paper cites Bayesian.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Bayesian

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.154759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.154759Z digest=sha256:92e51e50aa07247e8d6aceb52188820a7b1ab3e58eb7197ae6839ff84336e6f1

Observation e9b61234-d434-42e3-8a60-3895c750da46 · outbound

This paper cites an unresolved cited work.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.158658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.158658Z digest=sha256:31dc4afb92887d0497f1de8e6e6ef2ce0bf2128b9b553de69c78e4f86ab34734

Observation a3fc8ad9-ee1e-4ecf-9665-b078e330162e · outbound

This paper cites Biosystems Engineering , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Biosystems Engineering , volume =

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.162328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.162328Z digest=sha256:5fffff31cf2fd9058281000f38e6bd48f1a46ae98f8a2088f6f81f55d025e50e

Observation e902a4c9-a716-480d-854f-37c30799c213 · outbound

This paper cites an unresolved cited work.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.165980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.165980Z digest=sha256:78d6c89b82533fb53d7958d4b2b9c5e6dc91d0e7c400cca8850ee5638738b694

Observation c8f30381-0abd-4391-9fff-d22a62174749 · outbound

This paper cites Artificial Intelligence , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Artificial Intelligence , volume =

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.169708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.169708Z digest=sha256:0c57894c37203d841e59a43b9fe95bf337f7bcedcf3ef19560adeaa383946b6f

Observation e8c9d1e0-a89c-44c1-a9aa-952f400a17ea · outbound

This paper cites and Williams, Christopher K.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Williams, Christopher K

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.174343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.174343Z digest=sha256:f36437d5ef0342f7453ce4f539855d22170d06e0d57e1d278923f59005f3ba37

Observation 35023d05-ca02-4085-aa4a-66e17edce225 · outbound

This paper cites The International Journal of Robotics Research , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression The International Journal of Robotics Research , volume =

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.178051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.178051Z digest=sha256:c62757d9a6057b354098d6db5900112934cab6c8819bacb5a7f2370c8ffbce00

Observation 3d504418-287e-4722-b214-d150302cf990 · outbound

This paper cites Mat\'ern.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Mat\'ern

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.182040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.182040Z digest=sha256:ad0ef0b9f19efca47b83044fa4c0a987ce6efb96338b9e5e7c073cdf1c757d0c

Observation 92b32ef9-e8dd-4d32-836c-106b71c39794 · outbound

This paper cites Trends in Cognitive Sciences , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Trends in Cognitive Sciences , volume =

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.185579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.185579Z digest=sha256:9d1a76ce52e1552a24c03668f62ac80c006ccb36d0fe90f0a15fabe92b22fbf5

Observation abe2d16f-45f5-450f-ad7a-d7f848a4d76d · outbound

This paper cites Generating Sentences from a Continuous Space , booktitle =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Generating Sentences from a Continuous Space , booktitle =

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.189358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.189358Z digest=sha256:2a56d3d40bf87ca095fb7935cbc5277c93829fb93ea86763c2264a612c303d3d

Observation 7f0825bf-34fd-4b10-a95d-72b4984fbfdf · outbound

This paper cites an unresolved cited work.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.193089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.193089Z digest=sha256:34da09196eaa524aff590981406ebc4143ee5deb2205b64571316e9197f1fd29

Observation 1c3631ab-42a5-44b1-9921-5c2b88a917d4 · outbound

This paper cites TurboMPC: Fast, Scalable, and Differentiable Model Predictive Control on the GPU.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression TurboMPC: Fast, Scalable, and Differentiable Model Predictive Control on the GPU

Reference 50

Resolution
metadata mismatch
local_arxiv, observed 2026-08-16T00:33:52.642368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T00:30:59.196743Z digest=sha256:01412803dade8388198cde131f5224923fffbe0cb69f610c852f3c921d74ad7e

Observation 7d3826d0-e88f-422c-94d9-185feafdb48c · outbound

This paper cites OpenAI Gym.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression OpenAI Gym

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.200663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.200663Z digest=sha256:a8dbf762a0bd40e4022d6a3fe5d543245fe48546d8594647349b20fce882b042

Observation 78c99434-e2ce-4f21-a957-bfa776f6b99f · outbound

This paper cites Risk Sensitive Path Integral Control.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Risk Sensitive Path Integral Control

Reference 52

Resolution
verified exact
local_arxiv, observed 2026-08-16T00:33:52.603533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T00:30:59.204838Z digest=sha256:12aabe8ce0eb5af979e50e9bccf943d010c614d1ba396dbfbe7a8ef370cb7e81

Observation 06aeb820-8713-4ced-91c1-df2aaf7d502b · outbound

This paper cites and Dhariwal, Prafulla and Neelakantan, Arvind and Shyam, Pranav and Sastry, Girish and Askell, Amanda and Agarwal, Sandhini and.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Dhariwal, Prafulla and Neelakantan, Arvind and Shyam, Pranav and Sastry, Girish and Askell, Amanda and Agarwal, Sandhini and

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.208640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.208640Z digest=sha256:ae94736de2754af195ec0609f166d1956c8113aad2eabd3caf445c7836061d91

Observation 06a447f0-81f2-430a-9451-29cb7777ac12 · outbound

This paper cites Scalable.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Scalable

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.212482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.212482Z digest=sha256:f99d044411cf072d06c45004fdf27c3233c5cbe08e5fda2db74f493b86bda29b

Observation 5df58548-a268-4fae-b4c0-ef1140c26e43 · outbound

This paper cites and Kim, Chang Sub and McGregor, Simon and Seth, Anil K.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Kim, Chang Sub and McGregor, Simon and Seth, Anil K

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.215614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.215614Z digest=sha256:a197216cb6197c6c0918eea7ca2df1a4c3b36e720a9973f4fbcce1749d9d12f7

Observation 575c6afe-390e-41f5-ab29-08966d62723b · outbound

This paper cites and Nguyen, Cuong V.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Nguyen, Cuong V

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.218763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.218763Z digest=sha256:c3d2f0a4fc9a70f31aba926a28fa4c7a48dbb9898dc70fb5d396a737064a55c9

Observation 6b703969-b08b-41bf-9ddd-7daaf9c8852e · outbound

This paper cites Finding the Outliers in Scanpath Data , booktitle =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Finding the Outliers in Scanpath Data , booktitle =

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.221726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.221726Z digest=sha256:e64aa5dedb46d506abcfeb65328bd963e332b939dda4d5578e45764d04828950

Observation 83f0d3a7-fa4f-4895-97e9-451fd91404a1 · outbound

This paper cites Exploration by Random Network Distillation.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Exploration by Random Network Distillation

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.224741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.224741Z digest=sha256:32c691eb5f76ac44d471fa1e8d626d58a1bed4f51d508c2538cfe013e0fc6df4

Observation 329747fa-8c01-4625-8d9d-8593a63f2f66 · outbound

This paper cites and Lee, Daniel and Goodrich, Ben and Betancourt, Michael and Brubaker, Marcus and Guo, Jiqiang and Li, Peter and Riddell, Allen , year = 2017, journal =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Lee, Daniel and Goodrich, Ben and Betancourt, Michael and Brubaker, Marcus and Guo, Jiqiang and Li, Peter and Riddell, Allen , year = 2017, journal =

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.228071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.228071Z digest=sha256:6e7284774b068a470294b990bab6db63e9434c265bca533fa9920b67ca1a83c9

Observation b0afe169-3bd3-4a9f-aae7-da81e0ebbbdd · outbound

This paper cites Lectures on Probability, Entropy, and Statistical Physics.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Lectures on Probability, Entropy, and Statistical Physics

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.231477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.231477Z digest=sha256:7bcc6bd587379b6f78a0d6db4d2666333d045ca1ef23109d705b439c9b498de2

Observation 7bf38d57-9ab1-4a39-b2f1-23e2ccff5082 · outbound

This paper cites Stochastic Versions of the Em Algorithm: An Experimental Study in the Mixture Case , shorttitle =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Stochastic Versions of the Em Algorithm: An Experimental Study in the Mixture Case , shorttitle =

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.234664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.234664Z digest=sha256:902eac4c584acd7e970159dc9495dd3ff12f805dac30fec06deb558fc28e3ab0

Observation ee56a86e-f2f4-4f33-875a-59daf5b49afd · outbound

This paper cites Branching.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Branching

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.238318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.238318Z digest=sha256:1a9e804dff85ec445758e6ea416c537cc02879c9c72cb1f06729b8254c07d4a0

Observation 2791dba5-974c-42d2-a616-19770d9e8f49 · outbound

This paper cites Muse: Text-To-Image Generation via Masked Generative Transformers.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Muse: Text-To-Image Generation via Masked Generative Transformers

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.242098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.242098Z digest=sha256:1e198fc417c58df3e8a01165869dbdca40b51211374a1db01a1e5c5a21e8adab

Observation 666ea9b8-1bff-4f47-a2e7-b3bccbb931f9 · outbound

This paper cites an unresolved cited work.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.246040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.246040Z digest=sha256:10db819367b592c89a4bf4a6f3ab3d8b30327cad8cb0d428a7f2933aaaec9b1e

Observation 1bcea0f1-d0ac-4f12-8b0f-578a76ba131d · outbound

This paper cites Physical Review E , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Physical Review E , volume =

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.249572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.249572Z digest=sha256:0c6499f903f03ba3d5f0ec2377f058cadd95a1503b28f307f8796eb98fa55b28

Observation 70b29ca3-7f42-415f-ba97-585e3c8634b4 · outbound

This paper cites Advances in Neural Information Processing Systems , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Advances in Neural Information Processing Systems , volume =

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.253297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.253297Z digest=sha256:33424db5ce86d49b7156238c3fcbf63be1aa8dcea5fdada3e7d42e963c898084

Observation 9543d3bc-051d-4f80-a4e2-5fe6c86e0e77 · outbound

This paper cites Diffusion Policy:.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Diffusion Policy:

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.256929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.256929Z digest=sha256:7de4d844e14fd88a943f27f36902b498bc5228ca2295b1d08f570bccabcbd25b

Observation d052467e-481e-4fc7-99fc-3df5d9d71ee1 · outbound

This paper cites International Journal of Systems Science , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression International Journal of Systems Science , volume =

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.260995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.260995Z digest=sha256:7f93ce83625b8a42a4ba09f3e16527a3ee1a671025d91702d6b0799093e7f4a3

Observation 4e8a901f-2ab0-4dd4-872b-a13f2d67e0ea · outbound

This paper cites Temporal.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Temporal

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.264650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.264650Z digest=sha256:6e230bbfb9ba4ba46bc37d6d0d758da6ce0fa55e87c7ca52e20184d34c96e3e2

Observation e30151d7-97e0-44db-bd24-e5d2cd9e2a0f · outbound

This paper cites an unresolved cited work.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.268305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.268305Z digest=sha256:fdfaa1721e51e871b8989a06f513956c96f60b607c8193763acdc0375a11f940

Observation 2e4fd6ec-6215-48e7-949c-303caed5eddc · outbound

This paper cites BaLoRA: Bayesian Low-Rank Adaptation of Large Scale Models.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression BaLoRA: Bayesian Low-Rank Adaptation of Large Scale Models

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.271872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.271872Z digest=sha256:dbaa39f79d19aaeec56b81d88dd8686b29b381729ec9c4d0c61a86160c62fb24

Observation d45817b6-14e3-40cf-98fe-4fae5a655bff · outbound

This paper cites International.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression International

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.275832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.275832Z digest=sha256:236e76d02431783b4114762863badcda13bc8844080237a314127e3ca60d1a97

Observation 4ff14446-7494-4d06-a91a-1f3dc4b32ea7 · outbound

This paper cites American journal of physics , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression American journal of physics , volume =

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.279399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.279399Z digest=sha256:e65e9c2b8ca9d8138e14fbfe8617e0c674a823f648c983295eefcce10270caab

Observation 3534d40a-0fd9-4b5e-ad10-3d9bf7bea36e · outbound

This paper cites and Heskes, T.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Heskes, T

Reference 74

Resolution
verified exact
doi, observed 2026-08-16T00:33:52.485301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T00:30:59.283040Z digest=sha256:fdfef119e5314a05cdd5527ca0df0a019841869c73874a11c5074ed8fd4ad518

Observation 4a016581-435c-4cc6-b2ac-d3e1209230ca · outbound

This paper cites and Ramaker, B.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Ramaker, B

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.286702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.286702Z digest=sha256:75579ccda0fd337aee7a6dd1f32bd6e49badfa90ff4d1515c13da4c323ad886c

Observation 404781a9-897f-4749-86cd-52d2274706da · outbound

This paper cites Active Inference on Discrete State-Spaces:.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Active Inference on Discrete State-Spaces:

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.290578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.290578Z digest=sha256:9ae42f65cf0ca1f79185cb671745d7b72b6844743c9f7488d0a969e11a5160f6

Observation a5133ff1-33e2-48b0-9116-09e546d53fdf · outbound

This paper cites Active Inference as a Model of Agency.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Active Inference as a Model of Agency

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.294178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.294178Z digest=sha256:c8f0bd4a58400e40ca044b6fccaba10f48a8fdf2ea8f49c96c1ab7068748491b

Observation 950c98c6-c1c0-4851-8c7f-49815242101d · outbound

This paper cites doi:10.5194/essd-15-317-2023 , urldate =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression doi:10.5194/essd-15-317-2023 , urldate =

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.298331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.298331Z digest=sha256:f7e128c694a1b4ab4efbd7f7ba007fd9b680b673a6b2c7f2a80d5d369f1c58a7

Observation 90f77a14-88b7-4c07-89ce-47f47df2f8f2 · outbound

This paper cites IEEE Transactions on Geoscience and Remote Sensing , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression IEEE Transactions on Geoscience and Remote Sensing , volume =

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.302173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.302173Z digest=sha256:f4723f50a6aba096d62455151a6f5c70ef4629300e6ee1b9369c10d23554b474

Observation 9e055e2d-46ac-4277-9221-b6e73197c823 · outbound

This paper cites and Gelfand, Alan E.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Gelfand, Alan E

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.305879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.305879Z digest=sha256:9e309573c6f34332e8e51d078f15a7d2715a7b66ab83a6b7e30622b156932242

Observation 70c545df-5285-45bf-954a-651624ae22fd · outbound

This paper cites Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.309715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.309715Z digest=sha256:6fe08f1af5a5762a20865499943367aae4c5e65c235519b0aee77b138be8b52a

Observation d43e56d3-bcb6-4dd8-9def-cc056996a682 · outbound

This paper cites Parallel.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Parallel

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.313365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.313365Z digest=sha256:3aaf3e7272f4f6b854d716f79411448369b735660cde55a62ba9eeb09c4e1472

Observation 4c8f05a8-1a00-4558-8482-837191b3e2eb · outbound

This paper cites , year = 2007, month = jun, pages =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression , year = 2007, month = jun, pages =

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.317048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.317048Z digest=sha256:83fbc94fcbf1323d9fb9420a4c01f660e72bc6a07e3aa6b7cd81ff0d97fd75d2

Observation ac32ef8d-49b7-4291-896a-7f25e175c679 · outbound

This paper cites doi:10.1109/MMAR.2012.6347921 , urldate =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression doi:10.1109/MMAR.2012.6347921 , urldate =

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.320781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.320781Z digest=sha256:f8fc5529c9d345278141801c9fda65afa9ecbd5def07f1085e3f782eafe11a78

Observation 9a71f651-fa4d-4289-9316-99e826ea7431 · outbound

This paper cites Theory of Probability:.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Theory of Probability:

Reference 85

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.324274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.324274Z digest=sha256:405e93565222f05a905444057176cbc53899666df390cc503ab05457886a96ef

Observation d3e915a9-845a-482b-8ba1-fe706121c72a · outbound

This paper cites Entropy , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Entropy , volume =

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.328092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.328092Z digest=sha256:4f2402d3704de0d696f0fddcb510b60724beddaa02b4e31ff80a449b87a2e2ec

Observation 9a31d015-1c6f-4bf4-a7f6-dee80a345c4d · outbound

This paper cites an unresolved cited work.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.332045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.332045Z digest=sha256:2c97b0a1c16bd72bb9d1076da13644f4c4f9603ec781e9baf1619cec9d2e69b7

Observation 5a853947-6a05-4430-8418-e0d854c02e0f · outbound

This paper cites Expected.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Expected

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.336461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.336461Z digest=sha256:d6b3cebdfb737d701c5e18ba71fa03ec631acfa2fa435c50251894cbb9e53968

Observation bb45f78b-b64c-4906-9676-a2544f276b5b · outbound

This paper cites Journal of neural engineering , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Journal of neural engineering , volume =

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.340069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.340069Z digest=sha256:c7e63573786dfd19dc51dd0775678a199fcce3a788af8283f6890f9a5049b31d

Observation 708036ed-cc4b-4bb5-9a62-9b8725e4461a · outbound

This paper cites TensorFlow Distributions.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression TensorFlow Distributions

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.343611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.343611Z digest=sha256:41d3add6b4be238c6a91fd80e3031efd80f75cebbff564a2463cddc262205287

Observation 5656e416-ca4a-4098-a893-29f8bdebed31 · outbound

This paper cites IJCAI : proceedings of the conference , volume =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression IJCAI : proceedings of the conference , volume =

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.346988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.346988Z digest=sha256:bfa25048e9abb110c26575b5f35ceb18da6534adb3b3a597d7c75f832a32643a

Observation 6ab4dca1-9a2d-42e8-813f-07e3b413d4a1 · outbound

This paper cites Stochastic.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Stochastic

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.350166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.350166Z digest=sha256:788c6d5011991039feaa62d53bacf843bf3f482660564371507b3fca527b885d

Observation db8b4143-f4db-4574-9fc3-a20f16e2c83a · outbound

This paper cites and Del Bello, U.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Del Bello, U

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.353104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.353104Z digest=sha256:2a5fe4e05f9ff28e37a50a268c24493bd68f2a0ad54af16f3c97c63e7dae6920

Observation 285a78d0-fdc9-460b-91b8-46a5daaf7ce2 · outbound

This paper cites RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.356197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.356197Z digest=sha256:77b6e36d89231c6924ca3b81e0c76250351d5b0fa6e2cf8272ec484401bbf204

Observation b4f59141-4755-467f-aa32-2e7fc5060c86 · outbound

This paper cites an unresolved cited work.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work

Reference 95

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.359547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.359547Z digest=sha256:c6865e82f548acf8126a3c3005cd5a55cd7388a3fdc6caed4261206208a3f6d7

Observation 5c24f3f0-9feb-46d6-a4d9-3e6f0db1a966 · outbound

This paper cites Optimal Learning:.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Optimal Learning:

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.362885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.362885Z digest=sha256:3c5ea138fd61daa4e2402f77c7c5e2f75208d78e0c688c780441e9153eebd2ea

Observation ebc38ef6-969a-4cd2-a6e5-2ff7e358c15c · outbound

This paper cites an unresolved cited work.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work

Reference 97

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.365952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.365952Z digest=sha256:707e47b57836ea147a2d6dcc43d73f54b01e1218e2c975f03063fc2427b94a4f

Observation a216f33d-49c6-4f50-9402-7c48329b7c46 · outbound

This paper cites and Choo, Xuan and Bekolay, Trevor and DeWolf, Travis and Tang, Yichuan and Rasmussen, Daniel , year = 2012, month = nov, journal =.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Choo, Xuan and Bekolay, Trevor and DeWolf, Travis and Tang, Yichuan and Rasmussen, Daniel , year = 2012, month = nov, journal =

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.368972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.368972Z digest=sha256:6f1481cd977f2e544664a8b27bf93614fd408b3a13fd604c34ab39f2dfe0a143

Observation fd174571-0244-4399-a8de-a133003556ab · outbound

This paper cites RvS: What is Essential for Offline RL via Supervised Learning?.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression RvS: What is Essential for Offline RL via Supervised Learning?

Reference 99

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.372776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.372776Z digest=sha256:7bf51015beb2b10fb64acf88191d680eff8f08c6f96fe36575b11d53be9710d7

Observation 8477a4ed-54a2-4f8b-80ff-b2e894eac574 · outbound

This paper cites Resolving uncertainty on the fly: Modeling adaptive driving behavior as active inference.

A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Resolving uncertainty on the fly: Modeling adaptive driving behavior as active inference

Reference 100

Resolution
unresolved
no resolver link, observed 2026-08-16T00:30:59.377062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:30:59.377062Z digest=sha256:6f53136b7e3cd0d548eb142b15d9dbba105be955aededff81f86773207a0109e

Pith citing papers

No inbound Pith citation observations are available.