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Paper Citation Record · LEDGER

RieszBoost: Gradient Boosting for Riesz Regression

As of 16 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 3 inbound Pith citation observations for arXiv:2501.04871.

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

pith.paper-citation-record.v1
2501.04871 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:29:07.899920Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T03:05:44.393410Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

37 of 37 outbound references displayed

  • verified exact1
  • verified fuzzy24
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 2e9f387f-a2f2-44ae-968c-5a5c578d48be · outbound

This paper cites Introductory Functional Analysis with Applications.

RieszBoost: Gradient Boosting for Riesz Regression Introductory Functional Analysis with Applications

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.565474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.759376Z digest=sha256:e9d4c7c91758a4c4857110ad8d8b6e4e2f40394af0ac2570f474aaaff3967227

Observation 9a948c9e-5a32-4f3f-bdcf-c629d6e3d31b · outbound

This paper cites Robins, Andrea Rotnitzky, and Lue Ping Zhao.

RieszBoost: Gradient Boosting for Riesz Regression Robins, Andrea Rotnitzky, and Lue Ping Zhao

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.555313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.764001Z digest=sha256:41bffb81a0bcf893c27cd00dfd05bc734644982c668a234ad188b96bec53a84c

Observation 3b579c07-decf-4142-9be0-acb92ff84bb4 · outbound

This paper cites Neyman’s Repeated Sampling Approach to Completely Randomized Experiments.

RieszBoost: Gradient Boosting for Riesz Regression Neyman’s Repeated Sampling Approach to Completely Randomized Experiments

Reference 3

Resolution
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raw_fallback, observed 2026-08-10T21:29:08.545055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.768151Z digest=sha256:06d91f75584eb7c01f023a5d4f8feeaf5003b9e8b04744f3953cf7d0f5aa4d7e

Observation 3c25fb1f-230f-44f5-9b15-b774036bcbfa · outbound

This paper cites Bickel, C.A.J.

RieszBoost: Gradient Boosting for Riesz Regression Bickel, C.A.J

Reference 4

Resolution
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raw_fallback, observed 2026-08-10T21:29:08.532832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.772713Z digest=sha256:b948a59907da686ec8e1e9558812f2bfcac72f28007e302bef045be2f0629503

Observation 76175793-4174-45bb-b572-e40dae7cd7d3 · outbound

This paper cites van der Laan and J.M.

RieszBoost: Gradient Boosting for Riesz Regression van der Laan and J.M

Reference 5

Resolution
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raw_fallback, observed 2026-08-10T21:29:08.519529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.776942Z digest=sha256:d175577942f20b9db3b9eb899defb2b93952d08f0222e968ec0bcbe6b47ef47e

Observation 69052b61-37d2-4d23-bd7a-0a015a0b4b08 · outbound

This paper cites an unresolved cited work.

RieszBoost: Gradient Boosting for Riesz Regression Unresolved cited work

Reference 6

Resolution
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raw_fallback, observed 2026-08-10T21:29:08.510088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.780910Z digest=sha256:7dee81b17a77c3af9eefb1ddddc3f45bf429b68a9e7d4fe3fc16a8afa6505bc4

Observation 26dd869f-8c9d-4d42-99fe-17665153d97c · outbound

This paper cites van der Vaart.

RieszBoost: Gradient Boosting for Riesz Regression van der Vaart

Reference 7

Resolution
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raw_fallback, observed 2026-08-10T21:29:08.498878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.785528Z digest=sha256:851c40e35fbea9d105d64666e3c1b478bd0149ffa0995fc4bb927c6cf3e18b92

Observation 3cd270c4-2407-4ac2-91ea-65e70af3801e · outbound

This paper cites Newey, and Rahul Singh.

RieszBoost: Gradient Boosting for Riesz Regression Newey, and Rahul Singh

Reference 8

Resolution
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no resolver link, observed 2026-08-10T21:29:07.789169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:29:07.789169Z digest=sha256:123cf92cb48416920ec27c3e6dae23e0f04f44d1ad895981f8a59c81bfb6f68c

Observation b28e401b-2d0a-48b3-a45b-761c152eddc4 · outbound

This paper cites van der Laan and Daniel Rubin.

RieszBoost: Gradient Boosting for Riesz Regression van der Laan and Daniel Rubin

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.485906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.793585Z digest=sha256:1775cafa626a94fdbd6704120fd9e641cb81565bb973ba45bc5fbd48df8f9a4e

Observation 78a55b26-f6ea-4d01-943d-34367bd5ef43 · outbound

This paper cites Longitudinal Generalizations of the Average Treatment Effect on the Treated for Multi-valued and Continuous Treatments.

RieszBoost: Gradient Boosting for Riesz Regression Longitudinal Generalizations of the Average Treatment Effect on the Treated for Multi-valued and Continuous Treatments

Reference 10

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no resolver link, observed 2026-08-10T21:29:07.797146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:29:07.797146Z digest=sha256:775424fafc79507852b46ade1557bc6c1fc0db770b21d503afc17ed642afa228

Observation 6bebe191-8c0d-448b-83e7-9cf18f3f557f · outbound

This paper cites Automatic Debiased Machine Learning via Riesz Regression.

RieszBoost: Gradient Boosting for Riesz Regression Automatic Debiased Machine Learning via Riesz Regression

Reference 11

Resolution
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no resolver link, observed 2026-08-10T21:29:07.801153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:29:07.801153Z digest=sha256:36022122c07d068803a4b28f7b6c9859627a72c535d177878af6f6bbcc7fa4ba

Observation 2e4e918d-5fbf-48b4-a209-fe334dce1e96 · outbound

This paper cites RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests.

RieszBoost: Gradient Boosting for Riesz Regression RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T21:29:07.806231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:29:07.806231Z digest=sha256:e10ee9a71141dd8ab924c510cd850b397f9eb7e48659e4fc61c5b9d7c0809020

Observation 959be986-1186-4828-8678-1a240ad59077 · outbound

This paper cites The Balancing Act in Causal Inference.

RieszBoost: Gradient Boosting for Riesz Regression The Balancing Act in Causal Inference

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T21:29:07.811813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:29:07.811813Z digest=sha256:bfc3fa268c59c48af641a613ba84f06667fe62b502b4133af4d95cd574b90e27

Observation 41de0f3c-bcbf-4457-8025-a20f541c0fa1 · outbound

This paper cites Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies.

RieszBoost: Gradient Boosting for Riesz Regression Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.474955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.816241Z digest=sha256:f3b0631d6fd6d4422dc45b9fe0b2cc45c40a01ed399edc5ee0ae3839f97e47ec

Observation b27eb44b-fd32-4390-a736-281240e6df1d · outbound

This paper cites Graham, Cristine Campos De Xavier Pinto, and Daniel Egel.

RieszBoost: Gradient Boosting for Riesz Regression Graham, Cristine Campos De Xavier Pinto, and Daniel Egel

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.463884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.819624Z digest=sha256:65049ed714c80cee23fcc294c1189a8daeaff9b34ae959d5ddc754ac39a1d00c

Observation 9f785b99-57fd-4ef4-9840-a52af5491929 · outbound

This paper cites Zubizarreta.

RieszBoost: Gradient Boosting for Riesz Regression Zubizarreta

Reference 16

Resolution
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no resolver link, observed 2026-08-10T21:29:07.822931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:29:07.822931Z digest=sha256:b8ae32f3c38c8ff9ac6dea62159724347b94cf8839a5e2c56e5e5d3b5410d2ae

Observation d23020bb-a57f-4fa7-81f7-7545189f7cda · outbound

This paper cites On the implied weights of linear regression for causal inference.

RieszBoost: Gradient Boosting for Riesz Regression On the implied weights of linear regression for causal inference

Reference 17

Resolution
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local_arxiv, observed 2026-08-10T21:29:08.154941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.826246Z digest=sha256:3362fce865627f8f2ffb161a219f47acf4934cf6e2404e97c739696d0d1f71dd

Observation 272a69e5-4e08-42e4-9344-042ba301fe16 · outbound

This paper cites Friedman.

RieszBoost: Gradient Boosting for Riesz Regression Friedman

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.452669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.830233Z digest=sha256:47efb1671a3a3daa2f4d2fa80b945f15b90b7e89ac45f565f59659b3cc34e2fe

Observation 33c922e9-a221-44c5-a81d-26c01c9180e9 · outbound

This paper cites An empirical comparison of supervised learning algorithms.

RieszBoost: Gradient Boosting for Riesz Regression An empirical comparison of supervised learning algorithms

Reference 19

Resolution
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raw_fallback, observed 2026-08-10T21:29:08.441075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.833559Z digest=sha256:b67be82fdae5acd28148f7878b97909aa7db8a38dc575ab4e25353dd412769c2

Observation 5d8c7c8b-dd83-44c1-815e-763681c546d6 · outbound

This paper cites XGBoost: A Scalable Tree Boosting System.

RieszBoost: Gradient Boosting for Riesz Regression XGBoost: A Scalable Tree Boosting System

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.428621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.836911Z digest=sha256:c559c8e82505bf93eeb8a6f7f119ce3f9b71d7071d99c67e97f78013cc85d3d3

Observation 34fb44fc-438c-4ddd-a879-083c9ac7c672 · outbound

This paper cites LightGBM: A Highly Efficient Gradient Boosting Decision Tree.

RieszBoost: Gradient Boosting for Riesz Regression LightGBM: A Highly Efficient Gradient Boosting Decision Tree

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.417991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.840619Z digest=sha256:487691959235d61f826f39a9b019e10b9bcb954fdeea15eb727fdc10f6cda455

Observation 15c8a5c4-cde5-4ec3-a20a-9b6e12551bf3 · outbound

This paper cites Tabular data: Deep learning is not all you need.

RieszBoost: Gradient Boosting for Riesz Regression Tabular data: Deep learning is not all you need

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.406625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.843779Z digest=sha256:ce707fb4e52b5a7c0715339aeebad32672234c155d39b28139593a4b24260390

Observation 7a69160c-b3e1-406b-8721-9f26edd5e9d0 · outbound

This paper cites When Do Neural Nets Outperform Boosted Trees on Tabular Data?.

RieszBoost: Gradient Boosting for Riesz Regression When Do Neural Nets Outperform Boosted Trees on Tabular Data?

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:29:07.846835Z digest=sha256:b83145949a07cbe72816f19116c03e6f669ff378be4b737c5034b39203a74b05

Observation d7ab311d-c648-4a15-9ec2-8ecdee3c9bd0 · outbound

This paper cites Deep Neural Networks and Tabular Data: A Survey.

RieszBoost: Gradient Boosting for Riesz Regression Deep Neural Networks and Tabular Data: A Survey

Reference 24

Resolution
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raw_fallback, observed 2026-08-10T21:29:08.395090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.851049Z digest=sha256:d963413772dd276fde5b8127998cdc50f9022da279fc7a331476093fa74263b6

Observation 96dd116f-bf01-4c1d-acd4-7edb9dbd722b · outbound

This paper cites Friedman.

RieszBoost: Gradient Boosting for Riesz Regression Friedman

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.384414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.854175Z digest=sha256:471b8644119ba9acdd279a80c35b36fdd00eeda79fd537b99fcc1ef4a3a0d7a6

Observation 799c5028-fc84-4991-9163-59f027317ff3 · outbound

This paper cites Population Intervention Causal Effects Based on Stochastic Interventions.

RieszBoost: Gradient Boosting for Riesz Regression Population Intervention Causal Effects Based on Stochastic Interventions

Reference 26

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no resolver link, observed 2026-08-10T21:29:07.857449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:29:07.857449Z digest=sha256:2817ce827a9346d4366a77e9eec3da8d16d20adee7aa291261aadd54d7ed28c7

Observation ede22892-1ce4-40cf-aada-6d792a960cc4 · outbound

This paper cites Hoffman, and Edward J.

RieszBoost: Gradient Boosting for Riesz Regression Hoffman, and Edward J

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T21:29:07.861431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:29:07.861431Z digest=sha256:7cddd970b332f0bf1d4d69c7f2d8766a1a0d7115a0848a44e04c27badccb98d7

Observation 29dfe643-eb2c-4bf1-807c-c06d3045b715 · outbound

This paper cites Asymptotic Theory for Cross-validated Tar- geted Maximum Likelihood Estimation.

RieszBoost: Gradient Boosting for Riesz Regression Asymptotic Theory for Cross-validated Tar- geted Maximum Likelihood Estimation

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.374085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.865105Z digest=sha256:af5ec430a34b689d19bd4635cdcdb14fd1605fd393d396a53f834e590a9b9f7b

Observation eb243796-da65-4c9c-af3c-f2fcc7f3188f · outbound

This paper cites Double/debiased machine learning for treatment and structural parameters.

RieszBoost: Gradient Boosting for Riesz Regression Double/debiased machine learning for treatment and structural parameters

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.362869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.869227Z digest=sha256:a7b253059cc1eb538be70e9b08550237ee243203abe0b68e458eff3619e5529b

Observation 82e70ca4-ae41-4fa7-8bf0-be885442658e · outbound

This paper cites Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension.

RieszBoost: Gradient Boosting for Riesz Regression Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension

Reference 30

Resolution
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no resolver link, observed 2026-08-10T21:29:07.872683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:29:07.872683Z digest=sha256:fd3188bf1586ddc6b98905c95bc9ae6b84afdc6d2fa7934fb5083c6eb08800d3

Observation eac2ca7c-7730-4527-87c1-13239157563b · outbound

This paper cites Smoothing noisy data with spline functions.

RieszBoost: Gradient Boosting for Riesz Regression Smoothing noisy data with spline functions

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.350893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.876825Z digest=sha256:7d686a019a7f7362e227c0c44447f3d5f05bcb8c21fb2b3f3c12b719ce412ca5

Observation feabfd17-5cdd-4ef2-9810-857e7b2a8771 · outbound

This paper cites Tibshirani.

RieszBoost: Gradient Boosting for Riesz Regression Tibshirani

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.337221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.880301Z digest=sha256:75aeeb233bb0936ce37530a994a5e7f05cb58d3cd84a8da38795b1db8b6f3ad7

Observation 24cc7773-15d5-47cc-8f3e-1b94f482ce71 · outbound

This paper cites Boosting with early stopping: Convergence and consistency.

RieszBoost: Gradient Boosting for Riesz Regression Boosting with early stopping: Convergence and consistency

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.325584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.884049Z digest=sha256:253a77d9ca8b1ad2b7eba8ba2bf53e0be62f92f779eaf1b7da7d84e9b3aa8c96

Observation 90544ba8-d2d8-4963-a204-c56c41321ca4 · outbound

This paper cites Lassoed Tree Boosting, December.

RieszBoost: Gradient Boosting for Riesz Regression Lassoed Tree Boosting, December

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.313695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.887637Z digest=sha256:3e8f549b926349e0270c2ad596817d0eee6abcc044292529afde64f9c1a47273

Observation c57c490e-e4bc-413c-921b-189e46c4fa02 · outbound

This paper cites van der Laan.

RieszBoost: Gradient Boosting for Riesz Regression van der Laan

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.301372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.894963Z digest=sha256:61ad9162896af81796c0f635e2e2236cd9ab6a616e961a2bd080a912e6694656

Observation 76880ea1-3c83-4e77-a1be-e846a6dd176b · outbound

This paper cites 1q. Therefore, to derive the EIF, we must take this dependency into consideration (e.g. using the delta method on the inverse probability parameter 1 PpA“1q and the “partial.

RieszBoost: Gradient Boosting for Riesz Regression 1q. Therefore, to derive the EIF, we must take this dependency into consideration (e.g. using the delta method on the inverse probability parameter 1 PpA“1q and the “partial

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:29:08.290378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:29:07.899920Z digest=sha256:9c9c5216ef4c1f0e9329cd73add9c0691d40c56b3a3056a4f2b8b6c3ae237b9b

Observation ec6e5174-7ea9-4cfe-88e8-377d9cd9c876 · outbound

This paper cites Lassoed Tree Boosting.

RieszBoost: Gradient Boosting for Riesz Regression Lassoed Tree Boosting

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-10T21:29:07.891060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:29:07.891060Z digest=sha256:0fab642f0e2bf7d47c93b2078be0b13f99f7f76f83d3d596ea8c0746d3b7a711

Pith citing papers

Observation 6f7e0dfa-0528-4fab-ac0d-24828ef3cc4f · inbound

Semi-Supervised Treatment Effect Estimation with Unlabeled Covariates for Prediction-Powered Causal Inference cites this paper.

Semi-Supervised Treatment Effect Estimation with Unlabeled Covariates for Prediction-Powered Causal Inference RieszBoost: Gradient Boosting for Riesz Regression

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-17T23:50:31.406420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-17T23:47:56.278028Z digest=sha256:94a593926b78a1047cec9d9d7b814ad43aa53f7934593590c5fe2efab7a8b1f2

Observation 4e67e016-b3c1-473d-8c3c-1266fff405f0 · inbound

A Riesz Representer Perspective on Targeted Learning cites this paper.

A Riesz Representer Perspective on Targeted Learning RieszBoost: Gradient Boosting for Riesz Regression

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-05-09T21:03:18.784236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-09T21:00:21.894827Z digest=sha256:8c34afd94ee4fa3f0391f8ba7c2d994077b64e5582f997fb8832514d22fc2f0b

Observation 12c0ee15-5ef4-4463-9b45-809ce41f39ad · inbound

Outcome-adapted Automatic Debiased Machine Learning cites this paper.

Outcome-adapted Automatic Debiased Machine Learning RieszBoost: Gradient Boosting for Riesz Regression

Reference 3

Resolution
unresolved
no resolver link, observed 2026-07-12T03:05:44.393410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T03:05:44.393410Z digest=sha256:ccc262ad98e63eb24c3f82130e272d77ad702fbf274578bf65a5abc757142552