Paper Citation Record · LEDGER

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis

As of 18 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2502.03755.

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pith.paper-citation-record.v1
2502.03755 v1

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Outbound references

Observation aa713d4f-8f51-4919-bbb1-00c42f71dc06 · outbound

This paper cites Mars’ surface radiation environment measured with the mars science laboratory’s curiosity rover,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Mars’ surface radiation environment measured with the mars science laboratory’s curiosity rover,

Reference 1

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Observation 05b53e71-225e-482e-88f8-d94ce97d7fbb · outbound

This paper cites The collinearity problem in linear regression. the partial least squares (pls) approach to generalized inverses,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis The collinearity problem in linear regression. the partial least squares (pls) approach to generalized inverses,

Reference 2

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Observation 636f1d12-651d-4995-91ad-50263098a9fb · outbound

This paper cites Partial least squares regression (plsr) applied to nir and hsi spectral data modeling to predict chemical properties of fish muscle,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Partial least squares regression (plsr) applied to nir and hsi spectral data modeling to predict chemical properties of fish muscle,

Reference 3

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This paper cites The prediction of soil chemical and physical properties from mid-infrared spectroscopy and combined partial least-squares regression and neural networks (pls-nn) analysis,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis The prediction of soil chemical and physical properties from mid-infrared spectroscopy and combined partial least-squares regression and neural networks (pls-nn) analysis,

Reference 4

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Observation 8b04733d-dc70-400d-9a82-a7e30e073ff3 · outbound

This paper cites Prediction of aged red wine aroma properties from aroma chemical composition. partial least squares regression models,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Prediction of aged red wine aroma properties from aroma chemical composition. partial least squares regression models,

Reference 5

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Observation 19f80e48-9eb6-442c-9fa3-bc62541f2cb5 · outbound

This paper cites Fractional-order derivative spectral transformations improved partial least squares regression estimation of photosynthetic capacity from hyperspectral reflectance,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Fractional-order derivative spectral transformations improved partial least squares regression estimation of photosynthetic capacity from hyperspectral reflectance,

Reference 6

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Observation b52b3439-432d-4196-bbf1-28b967929b48 · outbound

This paper cites Using partial least squares-artificial neural network for inversion of inland water chlorophyll-a,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Using partial least squares-artificial neural network for inversion of inland water chlorophyll-a,

Reference 7

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This paper cites Multivariate analysis of remote laser-induced breakdown spectroscopy spectra using partial least squares, principal component analysis, and related techniques,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Multivariate analysis of remote laser-induced breakdown spectroscopy spectra using partial least squares, principal component analysis, and related techniques,

Reference 8

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Observation ffabc558-4b3e-4dde-b0d5-88ee813bcfbb · outbound

This paper cites Overview of the planetary data system,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Overview of the planetary data system,

Reference 9

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Observation 2ef1ff45-669f-4c21-83e6-36e9063d51cf · outbound

This paper cites A review on object detection based on deep convolutional neural networks for autonomous driving,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis A review on object detection based on deep convolutional neural networks for autonomous driving,

Reference 10

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This paper cites Face recognition based on convolutional neural network,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Face recognition based on convolutional neural network,

Reference 11

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This paper cites Medical image analysis using convolutional neural net- works: a review,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Medical image analysis using convolutional neural net- works: a review,

Reference 12

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Observation b058c7ee-9b12-400b-a556-e6b1237f47da · outbound

This paper cites Convolutional neural networks for vibrational spec- troscopic data analysis,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Convolutional neural networks for vibrational spec- troscopic data analysis,

Reference 13

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Observation 6be819d5-315b-42c4-8f65-0d667c3af7df · outbound

This paper cites Automated spectroscopic mod- elling with optimised convolutional neural networks,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Automated spectroscopic mod- elling with optimised convolutional neural networks,

Reference 14

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Observation 5b7702e7-d3e8-49b4-a2a0-afb6cd0c16e4 · outbound

This paper cites Deep learning spectroscopy: Neural networks for molecular excitation spectra,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Deep learning spectroscopy: Neural networks for molecular excitation spectra,

Reference 15

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This paper cites Character-level convolutional net- works for text classification,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Character-level convolutional net- works for text classification,

Reference 16

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This paper cites On measures of entropy and information,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis On measures of entropy and information,

Reference 17

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This paper cites On the solution of ill-posed problems and the method of regularization,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis On the solution of ill-posed problems and the method of regularization,

Reference 18

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Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Dropout training as adaptive regularization,

Reference 19

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Observation 242270a8-180e-48be-a03f-8ba0a14067ee · outbound

This paper cites Regularization via structural label smoothing,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Regularization via structural label smoothing,

Reference 20

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This paper cites Rethinking the inception architecture for computer vision,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Rethinking the inception architecture for computer vision,

Reference 21

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Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Learning repre- sentations by back-propagating errors,

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This paper cites Empirically estimable classification bounds based on a nonparametric divergence measure,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Empirically estimable classification bounds based on a nonparametric divergence measure,

Reference 23

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This paper cites Re- calibration of the mars science laboratory chemcam instrument with an 11 expanded geochemical database,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Re- calibration of the mars science laboratory chemcam instrument with an 11 expanded geochemical database,

Reference 24

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This paper cites Empirical risk minimization with f-divergence regularization in statistical learning,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Empirical risk minimization with f-divergence regularization in statistical learning,

Reference 25

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This paper cites Posterior Differential Regularization with f-divergence for Improving Model Robustness.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Posterior Differential Regularization with f-divergence for Improving Model Robustness

Reference 26

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This paper cites Learning fair classifiers via min-max f- divergence regularization,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Learning fair classifiers via min-max f- divergence regularization,

Reference 27

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This paper cites Multivariate f-divergence estimation with confidence,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Multivariate f-divergence estimation with confidence,

Reference 28

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Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Practical and consistent estimation of f-divergences,

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This paper cites f-divergence estimation and two-sample homogeneity test under semiparametric density-ratio models,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis f-divergence estimation and two-sample homogeneity test under semiparametric density-ratio models,

Reference 30

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This paper cites Empirical non-parametric estimation of the fisher information,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Empirical non-parametric estimation of the fisher information,

Reference 31

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This paper cites A multivariate two-sample test based on the number of nearest neighbor type coincidences,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis A multivariate two-sample test based on the number of nearest neighbor type coincidences,

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Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis On the multivariate runs test,

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Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Learning Implicit Generative Models Using Differentiable Graph Tests

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This paper cites Systems engineering the curiosity rover: A retrospective,.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Systems engineering the curiosity rover: A retrospective,

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Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis The mars 2020 engineering cameras and microphone on the perseverance rover: A next-generation imaging system for mars exploration,

Reference 36

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Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis The chemcam instrument suite on the mars science laboratory (msl) rover: Science objectives and mast unit description,

Reference 37

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Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis The supercam instrument suite on the mars 2020 rover: Science objectives and mast- unit description,

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This paper cites ADADELTA: An Adaptive Learning Rate Method.

Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis ADADELTA: An Adaptive Learning Rate Method

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Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis Dropout: a simple way to prevent neural networks from over- fitting,

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