Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data | Paper Citation Record

Observation 18d60e49-4b9f-4c92-9bdc-ea62ee433e49 · outbound

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Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Unresolved cited work

Reference 1

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Observation b4976d20-bdf0-4601-a32e-84a9ade59128 · outbound

This paper cites Lifecycle bias in estimates of intergenerational earnings persistence,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Lifecycle bias in estimates of intergenerational earnings persistence,

Reference 2

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This paper cites The era-40 re-analysis,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data The era-40 re-analysis,

Reference 3

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This paper cites Changes in the duration of european wet and dry spells during the last 60 years,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Changes in the duration of european wet and dry spells during the last 60 years,

Reference 4

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Observation 58a5e374-c53b-41d8-bffb-102f7f5affe4 · outbound

This paper cites Instruments for causal inference: an epidemiologist’s dream?.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Instruments for causal inference: an epidemiologist’s dream?

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.828937Z

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Observation 272266f4-93de-4c85-8bb2-3252e0c5dadc · outbound

This paper cites Causal inference from complex longitudinal data,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Causal inference from complex longitudinal data,

Reference 6

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Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:24:27.794643Z

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Observation 7f7c5db8-8815-47e7-953f-1de1b35c0606 · outbound

This paper cites Data-driven causal effect estimation based on graphical causal modelling: A survey,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Data-driven causal effect estimation based on graphical causal modelling: A survey,

Reference 8

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Observation b29dafe9-9058-42c2-89ca-e3507e8628b2 · outbound

This paper cites Marginal structural models to estimate the causal effect of zidovudine on the survival of hiv-positive men,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Marginal structural models to estimate the causal effect of zidovudine on the survival of hiv-positive men,

Reference 9

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Observation 219d8d68-b188-493c-83da-4a2ee1a33127 · outbound

This paper cites Estimating counterfactual treatment outcomes over time through adversarially balanced representations,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Estimating counterfactual treatment outcomes over time through adversarially balanced representations,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.741162Z

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This paper cites Time series deconfounder: Estimating treatment effects over time in the presence of hidden confounders,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Time series deconfounder: Estimating treatment effects over time in the presence of hidden confounders,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.724764Z

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Observation 87d2df79-1983-460c-9c02-f4db6a41e57c · outbound

This paper cites Instrumental variable estimation of the marginal structural cox model for time-varying treatments,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Instrumental variable estimation of the marginal structural cox model for time-varying treatments,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.707229Z

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This paper cites Instrumental variable estimation of marginal structural mean models for time-varying treatment,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Instrumental variable estimation of marginal structural mean models for time-varying treatment,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.689234Z

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Observation 6cb808bf-e7e8-40d9-97c9-b6b7adde4725 · outbound

This paper cites Estimating average causal effects from patient trajectories,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Estimating average causal effects from patient trajectories,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.671097Z

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Observation 341f65f1-204f-43cd-99d2-283f3625178b · outbound

This paper cites Estimating treatment effects from irregular time series observations with hidden confounders,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Estimating treatment effects from irregular time series observations with hidden confounders,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.653034Z

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Observation 419015a4-7ad1-4e40-bf8d-a9ccff8e5299 · outbound

This paper cites Causal transformer for estimating counterfactual outcomes,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Causal transformer for estimating counterfactual outcomes,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.636495Z

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Observation 4bebf21c-c89b-4377-9366-bbb191a7d497 · outbound

This paper cites Instrumental variable estimation for causal inference in longitudinal data with time-dependent latent confounders,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Instrumental variable estimation for causal inference in longitudinal data with time-dependent latent confounders,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.617732Z

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Observation eb3af2c1-cf72-4166-baec-630a533e1630 · outbound

This paper cites Marginal structural models and causal inference in epidemiology,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Marginal structural models and causal inference in epidemiology,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.600382Z

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Observation ede4d513-3b65-4e2a-a0ab-6847b968ae74 · outbound

This paper cites Pearl, Causality.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Pearl, Causality

Reference 19

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This paper cites Separators and adjustment sets in causal graphs: Complete criteria and an algorithmic framework,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Separators and adjustment sets in causal graphs: Complete criteria and an algorithmic framework,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.571226Z

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Observation d8bc427d-8a61-4a30-b311-e940781271f6 · outbound

This paper cites Deep IV: A flexible approach for counter- factual prediction,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Deep IV: A flexible approach for counter- factual prediction,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.542908Z

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Observation be5dbfd7-2212-4ee4-8960-63d4545e2f0e · outbound

This paper cites Causal inference with conditional instruments using deep generative models,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Causal inference with conditional instruments using deep generative models,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.523670Z

Source-reported events for the cited work

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Observation f91a6f21-d45f-4e09-b514-89b1f4c76879 · outbound

This paper cites Two-stage least squares estimation of average causal effects in models with variable treatment intensity,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Two-stage least squares estimation of average causal effects in models with variable treatment intensity,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.499682Z

Source-reported events for the cited work

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Observation 0a6d9a34-a2b1-4c40-8c7e-19ac6850ba46 · outbound

This paper cites Generalized instrumental variables,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Generalized instrumental variables,

Reference 24

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Observation 4a26f773-ecbb-419e-809c-2d625f7d1de9 · outbound

This paper cites Auto IV: counterfactual prediction via automatic instrumental variable decomposition,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Auto IV: counterfactual prediction via automatic instrumental variable decomposition,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.460443Z

Source-reported events for the cited work

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Observation 38e5f10b-bb2f-4811-84c9-e2f1b703c33d · outbound

This paper cites Peters, D.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Peters, D

Reference 26

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Observation d849303c-09af-41fb-af65-590f5b8e4b38 · outbound

This paper cites Long short-term memory,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Long short-term memory,

Reference 27

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This paper cites Auto-Encoding Variational Bayes.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Auto-Encoding Variational Bayes

Reference 28

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Observation 784461ca-a25f-4488-84cd-816b0a83f216 · outbound

This paper cites Learning structured output representation using deep conditional generative models,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Learning structured output representation using deep conditional generative models,

Reference 29

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This paper cites an unresolved cited work.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Unresolved cited work

Reference 30

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Observation 3a77d2ec-3813-41f4-a49b-b61a57a18903 · outbound

This paper cites Marginal structural models versus structural nested mod- els as tools for causal inference,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Marginal structural models versus structural nested mod- els as tools for causal inference,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.371718Z

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Observation d2ddc728-3ff1-4c8e-b98a-d9579ccdf540 · outbound

This paper cites Inference on heterogeneous treatment effects in high-dimensional dynamic panels under weak dependence,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Inference on heterogeneous treatment effects in high-dimensional dynamic panels under weak dependence,

Reference 32

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Observation f013d3bd-fdbf-4a97-8528-f34b9688c743 · outbound

This paper cites CTP:A Causal Interpretable Model for Non-Communicable Disease Progression Prediction.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data CTP:A Causal Interpretable Model for Non-Communicable Disease Progression Prediction

Reference 33

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Observation 17bb5a4f-5a18-4c84-9634-933fa815dea7 · outbound

This paper cites Identifying Causal Effects using Instrumental Time Series: Nuisance IV and Correcting for the Past.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Identifying Causal Effects using Instrumental Time Series: Nuisance IV and Correcting for the Past

Reference 34

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This paper cites Measurement bias and effect restoration in causal inference,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Measurement bias and effect restoration in causal inference,

Reference 35

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Observation 30ee5ca6-429a-4d98-a9ce-8ffd52b99d52 · outbound

This paper cites Identifying causal effects with proxy variables of an unmeasured confounder,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Identifying causal effects with proxy variables of an unmeasured confounder,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.193353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1ad4230e-c118-4b0c-8c7b-b76e32857094 · outbound

This paper cites Causal effect inference with deep latent- variable models,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Causal effect inference with deep latent- variable models,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.170962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 812edf83-87bf-4356-906d-a0672b217525 · outbound

This paper cites An introduction to variational autoencoders,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data An introduction to variational autoencoders,

Reference 38

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This paper cites Treatment effect estimation with dis- entangled latent factors,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Treatment effect estimation with dis- entangled latent factors,

Reference 39

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d0522bbc-52a8-4066-8caa-8754e65bc6fc · outbound

This paper cites The blessings of multiple causes,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data The blessings of multiple causes,

Reference 40

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b691843b-73a1-453e-90b4-d66736f603ee · outbound

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

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Double/debiased machine learning for treatment and structural parameters,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.093745Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation faa50351-2b1b-4ea0-92ad-a2d892fdfb4c · outbound

This paper cites Generalized random forests,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Generalized random forests,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.072556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b2ecd6e0-2af0-4636-8fe6-811d23b2ca5b · outbound

This paper cites Quasi-oracle estimation of heterogeneous treat- ment effects,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Quasi-oracle estimation of heterogeneous treat- ment effects,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.049813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 154e666f-52f1-4c78-a0fc-b923f09d1a6f · outbound

This paper cites Metalearners for estimating heteroge- neous treatment effects using machine learning,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Metalearners for estimating heteroge- neous treatment effects using machine learning,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.027963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d043222d-8bba-4f59-a40d-270fd7cab83e · outbound

This paper cites Marginal structural models to estimate the joint causal effect of nonrandomized treatments,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Marginal structural models to estimate the joint causal effect of nonrandomized treatments,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:27.004202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2b124123-0442-4fcd-ab30-eee5160c0793 · outbound

This paper cites Forecasting treatment responses over time using recurrent marginal structural networks,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Forecasting treatment responses over time using recurrent marginal structural networks,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:26.982367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d4be4ccf-9948-4e91-8cb6-0788bc16a3e5 · outbound

This paper cites EconML: A Python Package for ML- Based Heterogeneous Treatment Effects Estimation,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data EconML: A Python Package for ML- Based Heterogeneous Treatment Effects Estimation,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:26.961774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 97fdc32d-be7e-4b8d-97ea-362e437acc62 · outbound

This paper cites TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T12:24:26.494590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ac3884b-95a5-48e2-a080-5ed5b38669f1 · outbound

This paper cites The ncep/ncar 40-year reanalysis project,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data The ncep/ncar 40-year reanalysis project,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:26.942480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a7ef6e30-4c85-466c-bd90-b6bc893c6b71 · outbound

This paper cites A european daily high-resolution gridded data set of surface temperature and precipitation for 1950–2006,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data A european daily high-resolution gridded data set of surface temperature and precipitation for 1950–2006,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:26.921256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 167f85b0-8771-4472-89a8-76fed960432d · outbound

This paper cites Temperature and cape dependence in observed and modelled convective precipitation over the united states,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Temperature and cape dependence in observed and modelled convective precipitation over the united states,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:26.898201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7a7ee88f-028e-419e-a425-c5eec99f73ac · outbound

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

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Estimating individual treatment effect: generalization bounds and algorithms,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:26.876512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 288cc0b2-976d-47c9-8d63-73b9de283ebd · outbound

This paper cites Disentangled representation for causal mediation analysis,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Disentangled representation for causal mediation analysis,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:26.853667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 35a46f10-a93d-4ba2-9b56-d890bccc2e05 · outbound

This paper cites Causal inference with conditional front-door adjustment and identifiable variational autoencoder,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Causal inference with conditional front-door adjustment and identifiable variational autoencoder,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:26.824459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1bfbb0e4-3f6d-422e-8307-af44937c5886 · outbound

This paper cites Conditional instrumental variable regression with representation learning for causal inference,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Conditional instrumental variable regression with representation learning for causal inference,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:26.799882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d2eed38b-a753-4955-9ab1-7b928af95ac6 · outbound

This paper cites Instrumental variables: an econometrician’s perspective,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Instrumental variables: an econometrician’s perspective,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:26.780253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d3e3b6d6-ef00-4378-86be-ca46caf5f1c0 · outbound

This paper cites A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:26.757993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 945de079-0aac-4621-b2d0-8cb480106fbd · outbound

This paper cites Instrumental variables estima- tion of exposure effects on a time-to-event endpoint using structural cumulative survival models,.

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data Instrumental variables estima- tion of exposure effects on a time-to-event endpoint using structural cumulative survival models,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:24:26.732934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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