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Source: paper_references, paper_reference_links, observed 2026-05-23T03:17:16.705851Z
Paper Citation Record · LEDGER
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts
As of 27 July 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2502.05157.
A citation records a reference. It does not transfer a finding from one paper to another.
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Pith citing papers itemized under the disclosed page cap.
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Source: cited_works
Reference resolution
42 of 42 outbound references displayed
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- verified fuzzy41
- unresolved0
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External citation measurements
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Outbound references
Observation 53195597-b9f5-45cf-b6f8-247e671734de · outbound
This paper cites Variational inference for nonparametric B ayesian quantile regression.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Variational inference for nonparametric B ayesian quantile regression
Reference 1
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 5ce4d940-5d7c-4029-a108-386328fcc566 · outbound
This paper cites Breiman, J.
Reference 2
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 01ec6c74-a0a0-4de9-b6f0-14f7a698a9bf · outbound
This paper cites Brehmer and Tilmann Gneiting.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Brehmer and Tilmann Gneiting
Reference 3
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation f71ba2f4-156d-4e08-bca0-30be72857aef · outbound
This paper cites Towards scalable quantile regression trees.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Towards scalable quantile regression trees
Reference 4
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 17ffd66a-a68d-47ef-bf32-d3fd2b02c0a8 · outbound
This paper cites Classification and regression trees.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Classification and regression trees
Reference 5
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation de2d7262-6b98-4228-970c-4a7f38078139 · outbound
This paper cites Ray, Tilmann Gneiting, and Nicholas G.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Ray, Tilmann Gneiting, and Nicholas G
Reference 6
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation ffd4b2c6-760e-408d-86a2-55aad9260cdd · outbound
This paper cites Fenchel- Y oung losses with skewed entropies for class-posterior probability estimation.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Fenchel- Y oung losses with skewed entropies for class-posterior probability estimation
Reference 7
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 0d173f28-fc16-4055-95a7-f05b0deecbf6 · outbound
This paper cites an unresolved cited work.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Unresolved cited work
Reference 8
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation a2a36f95-979f-4289-9a32-62ef187893ca · outbound
This paper cites ACCRUE: A ccurate and reliable uncertainty estimate in deterministic models.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts ACCRUE: A ccurate and reliable uncertainty estimate in deterministic models
Reference 9
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 93c76c1c-eaf4-49c7-a8a3-b29890b94d09 · outbound
This paper cites Distributional conformal prediction.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Distributional conformal prediction
Reference 10
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation d61bcc5e-52d2-4f23-927d-48d2ab86a799 · outbound
This paper cites an unresolved cited work.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Unresolved cited work
Reference 11
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation bc946836-37a8-4cd4-ac55-941e3c61c646 · outbound
This paper cites Bayesian density regression.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Bayesian density regression
Reference 12
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 49c74e4c-3904-4689-8396-55b74a1eefda · outbound
This paper cites an unresolved cited work.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Unresolved cited work
Reference 13
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 6999633a-93ae-426b-a308-0602bbf7ea48 · outbound
This paper cites Gr \"u nwald and A.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Gr \"u nwald and A
Reference 14
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation b9beedf9-c0ae-436c-8d29-f85cf70b209c · outbound
This paper cites Nested conformal prediction and quantile out-of-bag ensemble methods.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Nested conformal prediction and quantile out-of-bag ensemble methods
Reference 15
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation cad26076-5dbf-4b89-8c78-42a1f7e5b6bd · outbound
This paper cites Fitting finite mixtures of generalized linear regressions in R.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Fitting finite mixtures of generalized linear regressions in R
Reference 16
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- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation cfe1a6e7-4f8e-42e4-8ee8-64f48bd300ea · outbound
This paper cites Strictly proper scoring rules, prediction, and estimation.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Strictly proper scoring rules, prediction, and estimation
Reference 17
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 614dea79-afa9-4c82-95d6-47107bb2fbcc · outbound
This paper cites Halim and F.
Reference 18
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- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation f6f25181-7332-4a46-a30e-4896cb620ecb · outbound
This paper cites Denoising diffusion probabilistic models.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Denoising diffusion probabilistic models
Reference 19
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 87d54548-a7b7-4e7e-b9b7-832844bad339 · outbound
This paper cites Hamilton and W Viscusi.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Hamilton and W Viscusi
Reference 20
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 5e7c78ba-6f84-4763-8ff5-9a199078c889 · outbound
This paper cites Evaluating probabilistic forecasts with scoringRules.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Evaluating probabilistic forecasts with scoringRules
Reference 21
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation ca94a7e2-3e64-476c-9cb5-5292013e78f6 · outbound
This paper cites A multiple quantile regression approach to the wind, solar, and price tracks of GEFCom2014.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts A multiple quantile regression approach to the wind, solar, and price tracks of GEFCom2014
Reference 22
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation b4a472a2-a166-4c91-b153-f006b8abb7a8 · outbound
This paper cites Regression quantiles.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Regression quantiles
Reference 23
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation c6c876c4-d99c-41b8-9c30-c0ba36d28e70 · outbound
This paper cites Normalizing flows: A n introduction and review of current methods.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Normalizing flows: A n introduction and review of current methods
Reference 24
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation f3473267-c698-498b-ba8b-1d23d978dcf9 · outbound
This paper cites Quantiles based personalized treatment selection for multivariate outcomes and multiple treatments.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Quantiles based personalized treatment selection for multivariate outcomes and multiple treatments
Reference 25
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 7e70f6ae-9769-4389-9dff-2532f4227bfd · outbound
This paper cites Rage against the mean – a review of distributional regression approaches.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Rage against the mean – a review of distributional regression approaches
Reference 26
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 0beddcaf-0d5d-4779-8eb4-5e8e66462802 · outbound
This paper cites Stepwise multiple quantile regression estimation using non-crossing constraints.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Stepwise multiple quantile regression estimation using non-crossing constraints
Reference 27
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- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation d420fea5-2a70-4364-ab47-2e3a85af2d6e · outbound
This paper cites Quantile regression forests.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Quantile regression forests
Reference 28
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- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation c446e75e-3456-46a5-8509-8c82eaa48d67 · outbound
This paper cites Handbook of data structures and applications.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Handbook of data structures and applications
Reference 29
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- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 52eb7a2b-6bb6-435f-9a44-e044275d1939 · outbound
This paper cites Generalized maximum entropy for supervised classification.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Generalized maximum entropy for supervised classification
Reference 30
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- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 10d7a243-f2c5-48d9-90c4-9789835f2a8b · outbound
This paper cites Nievergelt and E.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Nievergelt and E
Reference 31
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 15feef24-fd20-4af8-89b2-09357546eb18 · outbound
This paper cites High-resolution image synthesis with latent diffusion models.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts High-resolution image synthesis with latent diffusion models
Reference 32
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation b178d5be-ab96-4de4-aae9-e2ca0713507a · outbound
This paper cites Handbook of quantile regression.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Handbook of quantile regression
Reference 33
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation d282fbdc-5b15-4a78-89da-be019df02ad9 · outbound
This paper cites Conformalized quantile regression.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Conformalized quantile regression
Reference 34
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 03ddf38b-da76-4534-802a-7eb33ad40f6a · outbound
This paper cites an unresolved cited work.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Unresolved cited work
Reference 35
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 379c63b0-acb1-4a87-8422-0dfd63f1c6c1 · outbound
This paper cites A comparison of some conformal quantile regression methods.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts A comparison of some conformal quantile regression methods
Reference 36
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 1a9b1b70-890f-43b1-ac1c-38b6e030327a · outbound
This paper cites Engression: Extrapolation through the lens of distributional regression.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Engression: Extrapolation through the lens of distributional regression
Reference 37
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- raw_fallback, observed 2026-05-23T03:17:27.616336Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation f0871fa5-a831-4309-8f3e-e2c244f55cde · outbound
This paper cites Bayesian nonparametric quantile regression using splines.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Bayesian nonparametric quantile regression using splines
Reference 38
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- raw_fallback, observed 2026-05-23T03:17:27.509870Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 8a9c4aed-6c65-471e-b4a5-f007835894a7 · outbound
This paper cites Le, Timothy D.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Le, Timothy D
Reference 39
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- verified fuzzy
- raw_fallback, observed 2026-05-23T03:17:27.546471Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation df8b7aef-49a6-4efe-8866-5c4e3d53f871 · outbound
This paper cites A review on quantile regression for stochastic computer experiments.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts A review on quantile regression for stochastic computer experiments
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T03:17:27.561592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 3bcd566a-0b7d-4e96-b20e-5206b07d777e · outbound
This paper cites Continuity of generalized entropy.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Continuity of generalized entropy
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T03:17:27.565448Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Observation 36c18489-2944-4a92-90bd-0853ced054c5 · outbound
This paper cites Regularized simultaneous model selection in multiple quantiles regression.
Efficient distributional regression trees learning algorithms for calibrated non-parametric probabilistic forecasts Regularized simultaneous model selection in multiple quantiles regression
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T03:17:27.580404Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.
Pith citing papers
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