Paper Citation Record · LEDGER

Neural Tangent Kernel: Convergence and Generalization in Neural Networks

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 38 inbound Pith citation observations for arXiv:1806.07572.

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pith.paper-citation-record.v1
1806.07572 v4

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measured 38 of 38 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 38 of 38 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:22:25.087828Z

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Source: arxiv_reference, observed 2026-07-04T08:19:44.369596Z

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Outbound references

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Pith citing papers

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Sharpness-Aware Minimization for Efficiently Improving Generalization cites this paper.

Sharpness-Aware Minimization for Efficiently Improving Generalization Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 23

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Convergence rates for gradient descent in the training of overparameterized artificial neural networks with piecewise affine activation cites this paper.

Convergence rates for gradient descent in the training of overparameterized artificial neural networks with piecewise affine activation Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 17

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Observation 5caa8a75-693a-4010-8e18-715d7dbc41d0 · inbound

Editing Models with Task Arithmetic cites this paper.

Editing Models with Task Arithmetic Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 41

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Observation 86ddc345-4824-4989-8860-15b13613e0b3 · inbound

Deep learning applied to computational mechanics: A comprehensive review, state of the art, and the classics cites this paper.

Deep learning applied to computational mechanics: A comprehensive review, state of the art, and the classics Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 234

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Observation e6d34117-bbce-48b5-a26b-612c62d25232 · inbound

Approximating Simple ReLU Networks based on Spectral Decomposition of Fisher Information cites this paper.

Approximating Simple ReLU Networks based on Spectral Decomposition of Fisher Information Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 4

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Observation bb277ef5-c440-4243-8801-ae2ca4e47a57 · inbound

Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood cites this paper.

Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 23

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Statistical Machine Learning for Astronomy -- A Textbook cites this paper.

Statistical Machine Learning for Astronomy -- A Textbook Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 1990

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On the Complexity-Faithfulness Trade-off of Gradient-Based Explanations cites this paper.

On the Complexity-Faithfulness Trade-off of Gradient-Based Explanations Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 28

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Is data-efficient learning feasible with quantum models? cites this paper.

Is data-efficient learning feasible with quantum models? Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 6

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A physics-informed neural network approach to the point defect model for electrochemical oxide film growth cites this paper.

A physics-informed neural network approach to the point defect model for electrochemical oxide film growth Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 28

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Observation b15c8ab1-15bc-47e7-a01c-fba8cd366172 · inbound

Quantitative Understanding of PDF Fits and their Uncertainties cites this paper.

Quantitative Understanding of PDF Fits and their Uncertainties Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 16

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Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues cites this paper.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 14

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Grokking as Dimensional Phase Transition in Neural Networks cites this paper.

Grokking as Dimensional Phase Transition in Neural Networks Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 15

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Dimensional Criticality at Grokking Across MLPs and Transformers cites this paper.

Dimensional Criticality at Grokking Across MLPs and Transformers Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 13

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Neural Networks Reveal a Universal Bias in Conformal Correlators cites this paper.

Neural Networks Reveal a Universal Bias in Conformal Correlators Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 26

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Observation c506e47a-6af2-4996-a521-bdcdf67c9f6d · inbound

Neural Networks Reveal a Universal Bias in Conformal Correlators cites this paper.

Neural Networks Reveal a Universal Bias in Conformal Correlators Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T15:55:38.507583Z

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Observation 3af1aec0-2660-43d9-873a-d2249cfb101f · inbound

Neural Spectral Bias and Conformal Correlators I: Introduction and Applications cites this paper.

Neural Spectral Bias and Conformal Correlators I: Introduction and Applications Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:11:08.714666Z

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Neural Spectral Bias and Conformal Correlators I: Introduction and Applications cites this paper.

Neural Spectral Bias and Conformal Correlators I: Introduction and Applications Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 23

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Criticality and Saturation in Orthogonal Neural Networks cites this paper.

Criticality and Saturation in Orthogonal Neural Networks Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 10

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Kernel-based guarantees for nonlinear parametric models in Bayesian optimization cites this paper.

Kernel-based guarantees for nonlinear parametric models in Bayesian optimization Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 8

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Neural Networks, Dispersion Relations and the Thermal Bootstrap cites this paper.

Neural Networks, Dispersion Relations and the Thermal Bootstrap Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-14T18:52:36.026297Z

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Observation 1afa586e-9080-4c59-a06b-a7a8b87790c9 · inbound

Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs cites this paper.

Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:12:50.697558Z

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Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs cites this paper.

Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 22

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Does Weight Decay Enhance Training Stability? cites this paper.

Does Weight Decay Enhance Training Stability? Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 14

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The Thermodynamic Costs of Simple Linear Regression cites this paper.

The Thermodynamic Costs of Simple Linear Regression Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 84

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Physics-Informed Neural Networks with Attention Feature Expansion for Monge-Amp\`ere Equations cites this paper.

Physics-Informed Neural Networks with Attention Feature Expansion for Monge-Amp\`ere Equations Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 26

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Outer-Momentum Restarting in High-Dimensional Two-Phase Optimization cites this paper.

Outer-Momentum Restarting in High-Dimensional Two-Phase Optimization Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 15

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Bayesian Inference with Shaped Deep Non-linear MLPs cites this paper.

Bayesian Inference with Shaped Deep Non-linear MLPs Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 13

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Theory of learning of high-dimensional controlled non-linear dynamical systems (I): models and methods cites this paper.

Theory of learning of high-dimensional controlled non-linear dynamical systems (I): models and methods Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 8

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Some Inverse Problems in Particle Physics cites this paper.

Some Inverse Problems in Particle Physics Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 24

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Integrating Out, Twice:The Open-System Case That Neural-Network Ensemble Theory Is Missing cites this paper.

Integrating Out, Twice:The Open-System Case That Neural-Network Ensemble Theory Is Missing Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 15

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Lectures on Semiclassical Methods for Composite Operators cites this paper.

Lectures on Semiclassical Methods for Composite Operators Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 117

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Learning from almost nothing: How neural networks survive heavy input corruption cites this paper.

Learning from almost nothing: How neural networks survive heavy input corruption Neural Tangent Kernel: Convergence and Generalization in Neural Networks

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Channel Location Constrains the Auditability of Subliminal Learning cites this paper.

Channel Location Constrains the Auditability of Subliminal Learning Neural Tangent Kernel: Convergence and Generalization in Neural Networks

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Pre-Strings Lectures on Artificial Intelligence cites this paper.

Pre-Strings Lectures on Artificial Intelligence Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 49

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Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations cites this paper.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 6

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Coupled by Design: Computing Kerr-Newman Quasinormal Modes with a Hybrid SpectralPINN Solver cites this paper.

Coupled by Design: Computing Kerr-Newman Quasinormal Modes with a Hybrid SpectralPINN Solver Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 39

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How Meta-Learning Shapes LoRA Adapter Geometry in Speech Deepfake Detection cites this paper.

How Meta-Learning Shapes LoRA Adapter Geometry in Speech Deepfake Detection Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 2018

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