Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T17:30:13.387444Z
Paper Citation Record · LEDGER
Probabilistic Pretraining for Neural Regression
As of 18 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 2 inbound Pith citation observations for arXiv:2508.16355.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T12:16:40.864431Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
58 of 58 outbound references displayed
- verified exact0
- verified fuzzy47
- unresolved10
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
0
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
Observation 2d8216a6-e434-4e3b-818e-ac724b552fcf · outbound
This paper cites KEEL data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework.
Probabilistic Pretraining for Neural Regression KEEL data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:23.377515Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 177817ee-8982-454a-b22a-39128a0fa5f4 · outbound
This paper cites 1st place solution for the regression with a flood prediction dataset.
Probabilistic Pretraining for Neural Regression 1st place solution for the regression with a flood prediction dataset
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:23.210550Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 92d66b43-9ab7-4ae3-8c03-32f2828c56b9 · outbound
This paper cites Chronos: Learning the Language of Time Series.
Probabilistic Pretraining for Neural Regression Chronos: Learning the Language of Time Series
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:30:10.006806Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00f9c0bc-20a1-4127-a0de-4f34376da26c · outbound
This paper cites Arik and Tomas Pfister.
Probabilistic Pretraining for Neural Regression Arik and Tomas Pfister
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:22.992594Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 45212f30-7307-4718-862b-1c78125b1e6b · outbound
This paper cites House rent prediction dataset, 2022.
Probabilistic Pretraining for Neural Regression House rent prediction dataset, 2022
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:22.804068Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9b8bfe97-19ef-4daf-b468-366248f156fc · outbound
This paper cites Random forests.
Probabilistic Pretraining for Neural Regression Random forests
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:30:10.250031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5034e300-aafb-4f29-87f6-8cc368a7ac80 · outbound
This paper cites Xgboost: A scalable tree boosting system.
Probabilistic Pretraining for Neural Regression Xgboost: A scalable tree boosting system
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:30:10.333300Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 45378ed8-c806-4d68-a26e-f59bf0e25d98 · outbound
This paper cites ps-s4e4: Eda | lightgbm | importance plots.
Probabilistic Pretraining for Neural Regression ps-s4e4: Eda | lightgbm | importance plots
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:22.620012Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8ba98eea-5e06-427c-940d-98ace40bf746 · outbound
This paper cites Ames, iowa: Alternative to the boston housing data as an end of semester regression project.
Probabilistic Pretraining for Neural Regression Ames, iowa: Alternative to the boston housing data as an end of semester regression project
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:22.429287Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9a4c9116-80b2-4e6d-a641-a1fcbaffb166 · outbound
This paper cites BERT : Pre-training of deep bidirectional transformers for language understanding.
Probabilistic Pretraining for Neural Regression BERT : Pre-training of deep bidirectional transformers for language understanding
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:22.231932Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 30a89797-35ec-44e4-b1e8-63a22d1efd6f · outbound
This paper cites Non-Uniform Random Variate Generation.
Probabilistic Pretraining for Neural Regression Non-Uniform Random Variate Generation
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:22.079679Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1ce35e98-abda-4f9f-93f2-adcca7b5b0e6 · outbound
This paper cites Flood prediction factors.
Probabilistic Pretraining for Neural Regression Flood prediction factors
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:21.752493Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c61fd81a-ff6e-404d-968b-b8e810e59713 · outbound
This paper cites Uci machine learning repository: Abalone data set, 2019.
Probabilistic Pretraining for Neural Regression Uci machine learning repository: Abalone data set, 2019
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:21.499417Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f16504e5-fc81-4f8f-8e25-15bcd900da7c · outbound
This paper cites Deep neural networks for estimation and inference.
Probabilistic Pretraining for Neural Regression Deep neural networks for estimation and inference
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:21.156623Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 14943201-7d05-4eef-9f32-a940f98d8215 · outbound
This paper cites an unresolved cited work.
Probabilistic Pretraining for Neural Regression Unresolved cited work
Reference 15
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T17:30:20.772196Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7d785a45-9ca2-4cd6-b3b5-60f7163dbb67 · outbound
This paper cites Neural Processes.
Probabilistic Pretraining for Neural Regression Neural Processes
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:30:10.991073Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6781db4d-f5bc-4e16-88d7-8e6ef2c5e347 · outbound
This paper cites Timegpt-1, 2023.
Probabilistic Pretraining for Neural Regression Timegpt-1, 2023
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:20.359906Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0907ccff-1238-4d0e-9846-c2e94bb766fe · outbound
This paper cites Comparing density forecasts using threshold-and quantile-weighted scoring rules.
Probabilistic Pretraining for Neural Regression Comparing density forecasts using threshold-and quantile-weighted scoring rules
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:20.069702Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7924e533-c85c-40ec-ad4c-125fec2f629d · outbound
This paper cites Why do tree-based models still outperform deep learning on typical tabular data? In Proc.
Probabilistic Pretraining for Neural Regression Why do tree-based models still outperform deep learning on typical tabular data? In Proc
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:19.876210Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a5a25a8d-8552-43dc-b4e6-84f7e47e968d · outbound
This paper cites 1st place solution for the regression with an abalone dataset competition.
Probabilistic Pretraining for Neural Regression 1st place solution for the regression with an abalone dataset competition
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:19.685287Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d02fbc4d-23eb-4d1d-a397-75d755f57df2 · outbound
This paper cites Tab PFN : A transformer that solves small tabular classification problems in a second.
Probabilistic Pretraining for Neural Regression Tab PFN : A transformer that solves small tabular classification problems in a second
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:19.481594Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 917e0ab5-0968-4bd3-b3fe-95e2c56b8006 · outbound
This paper cites TabTransformer : Tabular data modeling using contextual embeddings.
Probabilistic Pretraining for Neural Regression TabTransformer : Tabular data modeling using contextual embeddings
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:19.370880Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f1d096a4-8d8b-4eca-b40f-ec68f2b5a53f · outbound
This paper cites Well-tuned simple nets excel on tabular datasets.
Probabilistic Pretraining for Neural Regression Well-tuned simple nets excel on tabular datasets
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:19.230340Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 635dc81c-7569-4679-a048-35f4dcd8e8ef · outbound
This paper cites Kaggle datasets, 2024.
Probabilistic Pretraining for Neural Regression Kaggle datasets, 2024
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:19.113734Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c41de291-070b-4c75-909a-5bc4bbd044e1 · outbound
This paper cites Linear convergence of gradient and proximal-gradient methods under the polyak-lojasiewicz condition.
Probabilistic Pretraining for Neural Regression Linear convergence of gradient and proximal-gradient methods under the polyak-lojasiewicz condition
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:18.995946Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 22949eee-d8df-447a-824f-7b80bd31bd4b · outbound
This paper cites Lightgbm: A highly efficient gradient boosting decision tree.
Probabilistic Pretraining for Neural Regression Lightgbm: A highly efficient gradient boosting decision tree
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:18.797617Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fde76c24-add7-455f-8031-7f7808876ac6 · outbound
This paper cites UCI machine learning repository, 2017.
Probabilistic Pretraining for Neural Regression UCI machine learning repository, 2017
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:18.601971Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d1c273db-f29f-4354-a24c-f923672f50b7 · outbound
This paper cites Transfer learning with deep tabular models.
Probabilistic Pretraining for Neural Regression Transfer learning with deep tabular models
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:18.446332Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fef218c8-bb73-4c28-ac4d-de116a9b46c2 · outbound
This paper cites Tabdpt: Scaling tabular foundation models.
Probabilistic Pretraining for Neural Regression Tabdpt: Scaling tabular foundation models
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:30:11.581467Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5f9c5294-4a62-4a46-b57f-91f0065fe5d9 · outbound
This paper cites Xgb|cat|lightgbm.
Probabilistic Pretraining for Neural Regression Xgb|cat|lightgbm
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:18.267661Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f5def6e7-2a91-4651-8592-85f7ad79cb18 · outbound
This paper cites Amazon price and product data: Electronic commerce, 2015.
Probabilistic Pretraining for Neural Regression Amazon price and product data: Electronic commerce, 2015
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:18.120326Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 20db6522-6741-4c69-a5d1-b489a1ab1bdb · outbound
This paper cites McInnes , J.
Probabilistic Pretraining for Neural Regression McInnes , J
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:17.939607Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a3b21994-d07e-4e16-9a51-ca713cd3525d · outbound
This paper cites Baseline v1 | catboost.
Probabilistic Pretraining for Neural Regression Baseline v1 | catboost
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:17.743603Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 800a31fc-9150-4969-a179-fa7835d8baa1 · outbound
This paper cites Transformers can do Bayesian inference.
Probabilistic Pretraining for Neural Regression Transformers can do Bayesian inference
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:17.603865Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9c5e93b0-163b-49d8-9a00-df71ea513753 · outbound
This paper cites TabPFN: A Transformer that solves small tabular classification problems in a second.
Probabilistic Pretraining for Neural Regression TabPFN: A Transformer that solves small tabular classification problems in a second
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:17.469870Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f9bcca93-f2ca-4b7a-9111-8383ab1f99c4 · outbound
This paper cites Occupancy flow: 4d reconstruction by learning particle dynamics.
Probabilistic Pretraining for Neural Regression Occupancy flow: 4d reconstruction by learning particle dynamics
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:17.304023Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 99396cc1-a2dc-4000-b042-7a7caac208dc · outbound
This paper cites Olson, William La Cava, Patryk Orzechowski, Ryan J.
Probabilistic Pretraining for Neural Regression Olson, William La Cava, Patryk Orzechowski, Ryan J
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:17.141426Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f63879a3-e6ba-431e-ad20-ce15194eeb46 · outbound
This paper cites Olson, William La Cava, Patryk Orzechowski, Ryan J.
Probabilistic Pretraining for Neural Regression Olson, William La Cava, Patryk Orzechowski, Ryan J
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:30:11.986364Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a58bdea-ef42-4323-b264-31e3bd95ba61 · outbound
This paper cites Wind dataset, n.d.
Probabilistic Pretraining for Neural Regression Wind dataset, n.d
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:16.988242Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8874574a-b577-4b63-87c1-22cea560dde0 · outbound
This paper cites Oreshkin, Florent Bocquelet, F \' e lix G.
Probabilistic Pretraining for Neural Regression Oreshkin, Florent Bocquelet, F \' e lix G
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:16.819576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7b9c0a42-c2ce-45b9-a3ad-01054ed51743 · outbound
This paper cites Film: Visual reasoning with a general conditioning layer.
Probabilistic Pretraining for Neural Regression Film: Visual reasoning with a general conditioning layer
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:16.649407Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a764af68-9f1b-4703-8f8d-8e33e0daec62 · outbound
This paper cites Catboost: unbiased boosting with categorical features, 2019.
Probabilistic Pretraining for Neural Regression Catboost: unbiased boosting with categorical features, 2019
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:16.490332Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 93efa09b-3820-4a18-9d7c-e8067ad59698 · outbound
This paper cites Qi, Hao Su, Kaichun Mo, and L.
Probabilistic Pretraining for Neural Regression Qi, Hao Su, Kaichun Mo, and L
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:16.308664Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9a34d602-4084-4cc4-ae04-9b4e8779eba3 · outbound
This paper cites Learning transferable visual models from natural language supervision.
Probabilistic Pretraining for Neural Regression Learning transferable visual models from natural language supervision
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:16.128499Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1a21ac27-f531-4587-a481-eebae14eb1e7 · outbound
This paper cites Dai, Nissan Hajaj, Michaela Hardt, Peter J.
Probabilistic Pretraining for Neural Regression Dai, Nissan Hajaj, Michaela Hardt, Peter J
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:15.970818Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e022b3d6-b5b0-42b4-a5fc-febc6c0716b5 · outbound
This paper cites Regression with an abalone dataset.
Probabilistic Pretraining for Neural Regression Regression with an abalone dataset
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:15.767429Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation beb74c02-972c-461e-a90c-b36674d8a828 · outbound
This paper cites Regression with a flood prediction dataset.
Probabilistic Pretraining for Neural Regression Regression with a flood prediction dataset
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:15.537989Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1c4e39e2-e8b0-4407-8f68-a9e4a0004124 · outbound
This paper cites PMLB v1.0: An open source dataset collection for benchmarking machine learning methods.
Probabilistic Pretraining for Neural Regression PMLB v1.0: An open source dataset collection for benchmarking machine learning methods
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:30:12.766670Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00238827-0ac1-4d0d-ae93-d53921cdb3ca · outbound
This paper cites Flood forecasting with xgboost.
Probabilistic Pretraining for Neural Regression Flood forecasting with xgboost
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:15.326449Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 33e34fce-2b7d-423f-a9bf-29129c59b5c7 · outbound
This paper cites Why nns is better than gbds? https://www.kaggle.com/competitions/playground-series-s4e4/discussion/496471\#2767909, 2024.
Probabilistic Pretraining for Neural Regression Why nns is better than gbds? https://www.kaggle.com/competitions/playground-series-s4e4/discussion/496471\#2767909, 2024
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:15.159275Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 436f1954-bc11-462b-9d88-006f5cc4c1d9 · outbound
This paper cites Any-Quantile Probabilistic Forecasting of Short-Term Electricity Demand.
Probabilistic Pretraining for Neural Regression Any-Quantile Probabilistic Forecasting of Short-Term Electricity Demand
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:30:12.943219Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7c717547-1f36-4171-a648-945795a238d7 · outbound
This paper cites an unresolved cited work.
Probabilistic Pretraining for Neural Regression Unresolved cited work
Reference 52
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T17:30:14.972516Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 74790b11-d629-424e-8b5c-d029a05beb8e · outbound
This paper cites Monocular, One-stage, Regression of Multiple 3D People.
Probabilistic Pretraining for Neural Regression Monocular, One-stage, Regression of Multiple 3D People
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:14.795057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 639d9f39-c78d-4aa9-b243-59b1e0d8a79d · outbound
This paper cites van Rijn, Bernd Bischl, and Luis Torgo.
Probabilistic Pretraining for Neural Regression van Rijn, Bernd Bischl, and Luis Torgo
Reference 54
- Resolution
- metadata mismatch
- raw_fallback, observed 2026-08-05T17:30:13.634328Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ac033d83-a6e5-480e-8beb-865fec1869de · outbound
This paper cites Attention is all you need.
Probabilistic Pretraining for Neural Regression Attention is all you need
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:14.559842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 79aff961-0786-4cbb-ba93-e65e5ed0dc22 · outbound
This paper cites S4e4 | abalone | catboost.
Probabilistic Pretraining for Neural Regression S4e4 | abalone | catboost
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:14.394928Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 05df92f6-53f3-43bf-bd62-15734e8bf9ca · outbound
This paper cites Deep sets.
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:14.217287Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0f9249dc-c62a-4414-8e6e-204c5e0428be · outbound
This paper cites Openfe: automated feature generation with expert-level performance.
Probabilistic Pretraining for Neural Regression Openfe: automated feature generation with expert-level performance
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T17:30:14.060658Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Pith citing papers
Observation a31613dc-6b12-403c-899c-43b146bfe8cf · inbound
AGNFormer I: Reconstruction of AGN spectra using a probabilistic transformer model cites this paper.
AGNFormer I: Reconstruction of AGN spectra using a probabilistic transformer model Probabilistic Pretraining for Neural Regression
Reference 67
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T12:16:34.627933Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e749632b-27a6-4606-ba89-10aed8270ac0 · inbound
AGNFormer I: Reconstruction of AGN spectra using a probabilistic transformer model cites this paper.
AGNFormer I: Reconstruction of AGN spectra using a probabilistic transformer model Probabilistic Pretraining for Neural Regression
Reference 112
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-01T12:18:29.828129Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.