Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression | Paper Citation Record

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This paper cites Efficient estimation of models with conditional moment restrictions containing unknown functions.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Efficient estimation of models with conditional moment restrictions containing unknown functions

Reference 1

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This paper cites Angrist and A.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Angrist and A

Reference 2

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This paper cites Identification and estimation of local average treatment effects, 1995.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Identification and estimation of local average treatment effects, 1995

Reference 3

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Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression On gradient regularizers for MMD GANs

Reference 4

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This paper cites On deep learning as a remedy for the curse of dimensionality in nonparametric regression.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression On deep learning as a remedy for the curse of dimensionality in nonparametric regression

Reference 5

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This paper cites Deep generalized method of moments for instrumental variable analysis.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Deep generalized method of moments for instrumental variable analysis

Reference 6

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This paper cites Inference on strongly identified functionals of weakly identified functions.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Inference on strongly identified functionals of weakly identified functions

Reference 7

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This paper cites Minimax instrumental variable regression and l2 convergence guarantees without identification or closedness.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Minimax instrumental variable regression and l2 convergence guarantees without identification or closedness

Reference 8

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This paper cites Source Condition Double Robust Inference on Functionals of Inverse Problems.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Source Condition Double Robust Inference on Functionals of Inverse Problems

Reference 9

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Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Unresolved cited work

Reference 10

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This paper cites Bissantz, T.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Bissantz, T

Reference 11

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This paper cites Semi-nonparametric IV estimation of shape-invariant Engel curves.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Semi-nonparametric IV estimation of shape-invariant Engel curves

Reference 12

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This paper cites Linear inverse problems in structural econometrics estimation based on spectral decomposition and regularization.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Linear inverse problems in structural econometrics estimation based on spectral decomposition and regularization

Reference 13

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This paper cites Large sample sieve estimation of semi-nonparametric models.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Large sample sieve estimation of semi-nonparametric models

Reference 14

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This paper cites Christensen.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Christensen

Reference 15

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This paper cites On rate optimality for ill-posed inverse problems in econometrics.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression On rate optimality for ill-posed inverse problems in econometrics

Reference 16

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This paper cites On instrumental variable regression for deep offline policy evaluation.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression On instrumental variable regression for deep offline policy evaluation

Reference 17

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This paper cites Darolles, Y.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Darolles, Y

Reference 18

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This paper cites On the approximation of functions by tanh neural networks.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression On the approximation of functions by tanh neural networks

Reference 19

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This paper cites De V ore and Vasil A.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression De V ore and Vasil A

Reference 20

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This paper cites Minimax estimation of conditional moment models.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Minimax estimation of conditional moment models

Reference 21

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This paper cites Donoho and Iain M.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Donoho and Iain M

Reference 22

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This paper cites Optimal adaptive sampling recovery.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Optimal adaptive sampling recovery

Reference 23

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This paper cites Continuous algorithms in adaptive sampling recovery.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Continuous algorithms in adaptive sampling recovery

Reference 24

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This paper cites Mathematical foundations of infinite-dimensional statistical models.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Mathematical foundations of infinite-dimensional statistical models

Reference 25

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This paper cites Conditional mean embeddings as regressors.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Conditional mean embeddings as regressors

Reference 26

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This paper cites Improved training of Wasserstein GANs.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Improved training of Wasserstein GANs

Reference 27

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Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Horowitz

Reference 28

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This paper cites Deep IV : a flexible approach for counterfactual prediction.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Deep IV : a flexible approach for counterfactual prediction

Reference 29

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This paper cites On the minimax optimality and superiority of deep neural network learning over sparse parameter spaces.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression On the minimax optimality and superiority of deep neural network learning over sparse parameter spaces

Reference 30

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This paper cites Applied nonparametric instrumental variables estimation.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Applied nonparametric instrumental variables estimation

Reference 31

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This paper cites A rigorous theory of conditional mean embeddings.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression A rigorous theory of conditional mean embeddings

Reference 32

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This paper cites Approximating smooth functions by deep neural networks with sigmoid activation function.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Approximating smooth functions by deep neural networks with sigmoid activation function

Reference 33

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This paper cites Optimal rates for regularized conditional mean embedding learning.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Optimal rates for regularized conditional mean embedding learning

Reference 34

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This paper cites Towards optimal S obolev norm rates for the vector-valued regularized least-squares algorithm.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Towards optimal S obolev norm rates for the vector-valued regularized least-squares algorithm

Reference 35

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Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Regularized DeepIV with Model Selection

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This paper cites Provably efficient neural estimation of structural equation models: An adversarial approach.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Provably efficient neural estimation of structural equation models: An adversarial approach

Reference 37

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This paper cites Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning

Reference 38

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This paper cites Nonparametric Instrumental Regression via Kernel Methods is Minimax Optimal.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Nonparametric Instrumental Regression via Kernel Methods is Minimax Optimal

Reference 39

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Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Unresolved cited work

Reference 40

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This paper cites Identification, Doubly Robust Estimation, and Semiparametric Efficiency Theory of Nonignorable Missing Data With a Shadow Variable.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Identification, Doubly Robust Estimation, and Semiparametric Efficiency Theory of Nonignorable Missing Data With a Shadow Variable

Reference 41

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This paper cites Nonparametric approximation of conditional expectation operators.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Nonparametric approximation of conditional expectation operators

Reference 42

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This paper cites Dual instrumental variable regression.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Dual instrumental variable regression

Reference 43

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This paper cites Regularization in H ilbert scales under general smoothing conditions.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Regularization in H ilbert scales under general smoothing conditions

Reference 44

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Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Unresolved cited work

Reference 45

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This paper cites Newey and James L.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Newey and James L

Reference 46

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This paper cites A measure-theoretic approach to kernel conditional mean embeddings.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression A measure-theoretic approach to kernel conditional mean embeddings

Reference 47

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Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Functional Bilevel Optimization for Machine Learning

Reference 48

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This paper cites Spectral Representation for Causal Estimation with Hidden Confounders.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Spectral Representation for Causal Estimation with Hidden Confounders

Reference 49

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This paper cites A case for new neural network smoothness constraints.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression A case for new neural network smoothness constraints

Reference 50

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This paper cites An unconditional basis in periodic spaces with dominating mixed smoothness properties.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression An unconditional basis in periodic spaces with dominating mixed smoothness properties

Reference 51

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This paper cites Nonparametric regression using deep neural networks with ReLU activation function.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Nonparametric regression using deep neural networks with ReLU activation function

Reference 52

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Observation 9e0cc0f3-8533-4ba7-a5a8-598e6c0a2515 · outbound

This paper cites Kernel instrumental variable regression.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Kernel instrumental variable regression

Reference 53

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This paper cites Robust large margin deep neural networks.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Robust large margin deep neural networks

Reference 54

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Observation ff570a95-930a-4249-a27f-56896bac4923 · outbound

This paper cites Hilbert space embeddings of conditional distributions with applications to dynamical systems.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Hilbert space embeddings of conditional distributions with applications to dynamical systems

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:29:12.467978Z

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This paper cites Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality

Reference 56

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This paper cites Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic B esov space.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic B esov space

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:29:12.445351Z

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This paper cites Theory of function spaces.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Theory of function spaces

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:29:12.434105Z

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This paper cites Finite Sample Analysis of Minimax Offline Reinforcement Learning: Completeness, Fast Rates and First-Order Efficiency.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Finite Sample Analysis of Minimax Offline Reinforcement Learning: Completeness, Fast Rates and First-Order Efficiency

Reference 59

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This paper cites Widths of embeddings in function spaces.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Widths of embeddings in function spaces

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:29:12.422345Z

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This paper cites Wainwright.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Wainwright

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:29:12.411464Z

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Observation 1c7c2bea-554d-456c-8c76-fcb2f5b93ea8 · outbound

This paper cites An instrumental variable approach for identification and estimation with nonignorable nonresponse.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression An instrumental variable approach for identification and estimation with nonignorable nonresponse

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:29:12.400683Z

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Observation 468ef4af-3ba9-45e6-8a51-2e74b7fc2330 · outbound

This paper cites Spectral Representation Learning for Conditional Moment Models.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Spectral Representation Learning for Conditional Moment Models

Reference 63

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Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Wasserman

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:29:12.389538Z

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Observation b6df8530-8775-419b-afb8-e7c3fb9ba6be · outbound

This paper cites Learning deep features in instrumental variable regression.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Learning deep features in instrumental variable regression

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:29:12.380236Z

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Observation 291e5013-f639-4a88-9b46-f4f45f066687 · outbound

This paper cites Information-theoretic determination of minimax rates of convergence.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Information-theoretic determination of minimax rates of convergence

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:29:12.369433Z

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Observation 85d5cd7f-57cc-455e-a6af-5a9c45297de9 · outbound

This paper cites Instrumental variable regression via kernel maximum moment loss.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Instrumental variable regression via kernel maximum moment loss

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:29:12.358002Z

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Observation 134bffe9-4be8-4393-87fb-c58c0788d411 · outbound

This paper cites Wavelet threshold estimation of a regression function with random design.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Wavelet threshold estimation of a regression function with random design

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:29:12.344789Z

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Observation aeea9a5c-65e9-4466-a2f0-6e4336ca507c · outbound

This paper cites write newline.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression write newline

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-10T21:29:12.165222Z

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Observation 1f700aa5-62d6-4ccb-b1b8-308d45efa50d · outbound

This paper cites @esa (Ref.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression @esa (Ref

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-10T21:29:12.169718Z

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Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Unresolved cited work

Reference 71

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Observation 96f308c3-c4d1-4a45-903d-a958002270be · outbound

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Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression Unresolved cited work

Reference 72

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