Paper Citation Record · LEDGER

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks

As of 7 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2507.12435.

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

pith.paper-citation-record.v1
2507.12435 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:53:01.694578Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

26 of 26 outbound references displayed

verified exact1
verified fuzzy12
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4fad86d0-4d2b-4f9d-958d-649932a71769 · outbound

This paper cites Double/debiased machine learning for treatment and structural parameters, 2018.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Double/debiased machine learning for treatment and structural parameters, 2018

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T16:52:59.957773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e806ae8-a3dc-4abf-a90c-d8416f2b6063 · outbound

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

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T16:53:02.392666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 26a9ad38-0852-42da-bc36-fb79c0b426aa · outbound

This paper cites Sieve plateau variance estimators: a new approach to confidence interval estimation for dependent data.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Sieve plateau variance estimators: a new approach to confidence interval estimation for dependent data

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:53:06.029398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0c802eee-b773-4244-a268-39fdc0f245e0 · outbound

This paper cites Bayesian nonparametric modeling for causal inference.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Bayesian nonparametric modeling for causal inference

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:53:05.839825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 426fb4ee-c9db-40df-8c9a-654448349d37 · outbound

This paper cites Springer, 2003.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Springer, 2003

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:53:05.623825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4389f7a4-583a-448d-815a-24fcffd9c063 · outbound

This paper cites Regularized Targeted Maximum Likelihood Estimation in Highly Adaptive Lasso Implied Working Models.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Regularized Targeted Maximum Likelihood Estimation in Highly Adaptive Lasso Implied Working Models

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:53:02.233023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b47d5cd9-ad20-4aea-8d80-3dcd91339abf · outbound

This paper cites One-step targeted maximum likelihood estima- tion for targeting cause-specific absolute risks and survival curves.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks One-step targeted maximum likelihood estima- tion for targeting cause-specific absolute risks and survival curves

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:53:05.375869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a655596f-497f-40ed-ae10-08c03e32edd2 · outbound

This paper cites Estimating individual treatment effect: generalization bounds and algorithms.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Estimating individual treatment effect: generalization bounds and algorithms

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:53:05.202478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9e295b05-b1d0-48bf-84d3-3caeb95065c2 · outbound

This paper cites Adapting neural networks for the estimation of treatment effects.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Adapting neural networks for the estimation of treatment effects

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:53:05.032876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b662bcd9-bf56-4e1b-b932-6fdbc626bc09 · outbound

This paper cites Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T16:53:00.702284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1d8f559-5eb8-47c8-acff-95df9dc8c292 · outbound

This paper cites Automatic debi- ased machine learning for smooth functionals of nonparametric m-estimands.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Automatic debi- ased machine learning for smooth functionals of nonparametric m-estimands

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T16:53:00.825849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c5715f5-298e-4caf-985f-f3531d4a0327 · outbound

This paper cites Adaptive debiased ma- chine learning using data-driven model selection techniques.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Adaptive debiased ma- chine learning using data-driven model selection techniques

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T16:53:00.882116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9adcfa4e-de20-49b8-b3c3-93774f20eeba · outbound

This paper cites One-step targeted minimum loss-based estimation based on universal least favorable one-dimensional submodels.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks One-step targeted minimum loss-based estimation based on universal least favorable one-dimensional submodels

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:53:04.812878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e594f13e-3d73-4a5d-9d89-afff56683a83 · outbound

This paper cites van der Laan and Sherri Rose.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks van der Laan and Sherri Rose

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:53:04.582212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 33738bc3-da92-43a6-9dcd-20b3ed225eca · outbound

This paper cites Response Surface B.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Response Surface B

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:53:04.417663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 64541206-b7fd-438d-9828-a9f44904e75f · outbound

This paper cites an unresolved cited work.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:53:04.182534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f0c512e0-e9a9-4d7b-b233-991e047e1587 · outbound

This paper cites an unresolved cited work.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:53:04.007534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 52786d03-fc47-41aa-b607-67cb3ff64b81 · outbound

This paper cites an unresolved cited work.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:53:03.789027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2a4339fb-23d0-4e85-b83d-0322a54646ff · outbound

This paper cites Comparison Methods.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Comparison Methods

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:53:03.620961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b17667ca-f1b0-4893-b516-49be2ce1e114 · outbound

This paper cites an unresolved cited work.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:53:03.443428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4ddf78c0-9a74-4c75-8390-ec9921d6fa16 · outbound

This paper cites an unresolved cited work.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:53:03.267073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4370d650-5efd-476f-84c8-10e105e26273 · outbound

This paper cites an unresolved cited work.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:53:03.102236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 04be2f71-b9ae-4d77-9077-ae1982247a78 · outbound

This paper cites ε-parametric submodel.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks ε-parametric submodel

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:53:02.882467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 78767e49-a055-43af-8061-d52df327a5da · outbound

This paper cites an unresolved cited work.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:53:02.755307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 982f7ce1-7472-4c83-88e2-1ae8d60cf6c4 · outbound

This paper cites an unresolved cited work.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:53:02.655682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 39a9e25f-9d1d-4151-8a91-956b7970e921 · outbound

This paper cites ε-fluctuations.

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks ε-fluctuations

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:53:02.561781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.