Optimal Linear Baseline Models for Scientific Machine Learning | Paper Citation Record

Observation 4ad45623-94e8-4351-81b7-34d8a9be5bd2 · outbound

This paper cites Deep Learning.

Optimal Linear Baseline Models for Scientific Machine Learning Deep Learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:27.922083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aace6cfe-24a6-45d3-8dc1-526333d78908 · outbound

This paper cites Surrogate and reduced-order modeling: a comparison of approaches for large- scale statistical inverse problems.

Optimal Linear Baseline Models for Scientific Machine Learning Surrogate and reduced-order modeling: a comparison of approaches for large- scale statistical inverse problems

Reference 2

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.926991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 32d1f40b-862d-4c6d-b8fd-c6fec96ea879 · outbound

This paper cites Kernel methods for surrogate modeling.

Optimal Linear Baseline Models for Scientific Machine Learning Kernel methods for surrogate modeling

Reference 3

Resolution: malformed identifier; no resolver link, observed 2026-08-05T23:19:27.931822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5204a460-7c39-4688-a721-86e048240123 · outbound

This paper cites Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.

Optimal Linear Baseline Models for Scientific Machine Learning Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 4

Resolution: malformed identifier; no resolver link, observed 2026-08-05T23:19:27.936023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77744e11-ac9b-4670-b5be-45c8408b9d7d · outbound

This paper cites Scientific machine learning through physics–informed neural networks: where we are and what’s next.

Optimal Linear Baseline Models for Scientific Machine Learning Scientific machine learning through physics–informed neural networks: where we are and what’s next

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:27.940518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55ba8118-48d7-414a-8bbf-77cb77896637 · outbound

This paper cites Deep neural network approach to forward-inverse problems.

Optimal Linear Baseline Models for Scientific Machine Learning Deep neural network approach to forward-inverse problems

Reference 6

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.909077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9ccbf369-0789-43c1-b602-4010cfbf442d · outbound

This paper cites Exact representation and efficient approximations of linear model predictive control laws via HardTanh type deep neural networks.

Optimal Linear Baseline Models for Scientific Machine Learning Exact representation and efficient approximations of linear model predictive control laws via HardTanh type deep neural networks

Reference 7

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T23:19:31.707394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4f23d69a-6df3-459b-b621-1dc7c9e99818 · outbound

This paper cites Inverse Problem Theory and Methods for Model Parameter Estimation.

Optimal Linear Baseline Models for Scientific Machine Learning Inverse Problem Theory and Methods for Model Parameter Estimation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:27.953274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a557606-b968-4e34-8850-f798a967b257 · outbound

This paper cites Discrete Inverse Problems: Insight and Algorithms.

Optimal Linear Baseline Models for Scientific Machine Learning Discrete Inverse Problems: Insight and Algorithms

Reference 9

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.892263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0371197c-2149-410b-b4b3-d9736388383b · outbound

This paper cites Sur les probl` emes aux d´ eriv´ ees partielles et leur signification physique.

Optimal Linear Baseline Models for Scientific Machine Learning Sur les probl` emes aux d´ eriv´ ees partielles et leur signification physique

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:27.961213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0799a102-0794-42da-93e1-93880cdac576 · outbound

This paper cites an unresolved cited work.

Optimal Linear Baseline Models for Scientific Machine Learning Unresolved cited work

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:27.964910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0dd34bde-f9fb-4d6d-988a-61881f68cdf1 · outbound

This paper cites Solving inverse problems using data-driven models.

Optimal Linear Baseline Models for Scientific Machine Learning Solving inverse problems using data-driven models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:27.968638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3688fec6-9955-4adb-a2dd-1bb4a1c32ccd · outbound

This paper cites Modern regularization methods for inverse problems.

Optimal Linear Baseline Models for Scientific Machine Learning Modern regularization methods for inverse problems

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:27.972953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 427926df-4b44-4579-aacc-61e26d7ebcbc · outbound

This paper cites Variational regularization in inverse problems and machine learning.

Optimal Linear Baseline Models for Scientific Machine Learning Variational regularization in inverse problems and machine learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:27.976707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3e36ae3-418d-4cf0-b542-998eb4aaa9c9 · outbound

This paper cites Solution paths of variational regularization methods for inverse problems.

Optimal Linear Baseline Models for Scientific Machine Learning Solution paths of variational regularization methods for inverse problems

Reference 15

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.856931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f0c8f78f-5311-4dfc-8478-5da0569408c6 · outbound

This paper cites Iterative regularization with a general penalty term-theory and application to L1 and TV regularization.

Optimal Linear Baseline Models for Scientific Machine Learning Iterative regularization with a general penalty term-theory and application to L1 and TV regularization

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:27.984589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aebf2278-7df0-4154-b819-38618535fd13 · outbound

This paper cites Iterative total variation schemes for nonlinear inverse prob- lems.

Optimal Linear Baseline Models for Scientific Machine Learning Iterative total variation schemes for nonlinear inverse prob- lems

Reference 17

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.844887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 69570893-2ef1-491d-b9d6-4dc89032bb1d · outbound

This paper cites Empirical Bayesian regularization of the inverse acoustic problem.

Optimal Linear Baseline Models for Scientific Machine Learning Empirical Bayesian regularization of the inverse acoustic problem

Reference 18

Resolution: malformed identifier; doi_truncated, observed 2026-08-05T23:19:28.829184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6fab6bf0-95f7-4891-aa9b-5fa4e2ce40fc · outbound

This paper cites Inverse problems: from regularization to Bayesian inference.

Optimal Linear Baseline Models for Scientific Machine Learning Inverse problems: from regularization to Bayesian inference

Reference 19

Resolution: malformed identifier; doi_truncated, observed 2026-08-05T23:19:28.817094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 70c4e035-c7be-401f-9fd0-1d1f6bf141cb · outbound

This paper cites Deep learning techniques for inverse problems in imaging.

Optimal Linear Baseline Models for Scientific Machine Learning Deep learning techniques for inverse problems in imaging

Reference 20

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T23:19:31.635605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 353c0c39-54af-49e5-9e08-8e77534d4282 · outbound

This paper cites Deep learning methods for inverse problems.

Optimal Linear Baseline Models for Scientific Machine Learning Deep learning methods for inverse problems

Reference 21

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.805672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 13d1ca5f-dac9-49b0-9c17-df32477c0cd9 · outbound

This paper cites Learning regularization parameters of inverse problems via deep neural networks.

Optimal Linear Baseline Models for Scientific Machine Learning Learning regularization parameters of inverse problems via deep neural networks

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.008338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 348ce7f8-618f-46f5-96e1-92cd88a76199 · outbound

This paper cites Deep convolutional neural network for inverse problems in imaging.

Optimal Linear Baseline Models for Scientific Machine Learning Deep convolutional neural network for inverse problems in imaging

Reference 23

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T23:19:31.525631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ae93c4af-55b6-4115-b454-4b0fe9f6722a · outbound

This paper cites Solving Inverse Problems in Medical Imaging with Score-Based Generative Models.

Optimal Linear Baseline Models for Scientific Machine Learning Solving Inverse Problems in Medical Imaging with Score-Based Generative Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.019948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d34c79c4-450f-4c28-8bbb-250bebd182f9 · outbound

This paper cites Convolutional neural networks for inverse problems in imaging: a review.

Optimal Linear Baseline Models for Scientific Machine Learning Convolutional neural networks for inverse problems in imaging: a review

Reference 25

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T23:19:31.448727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 46c8dade-e270-4bf6-8fe5-bd81a10ecdd9 · outbound

This paper cites Using deep neural networks for inverse problems in imaging: beyond analytical methods.

Optimal Linear Baseline Models for Scientific Machine Learning Using deep neural networks for inverse problems in imaging: beyond analytical methods

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.030323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b56238f7-4133-4b63-bf8b-2c16bc54900a · outbound

This paper cites Deep magnetic resonance image reconstruction: inverse problems meet neural networks.

Optimal Linear Baseline Models for Scientific Machine Learning Deep magnetic resonance image reconstruction: inverse problems meet neural networks

Reference 27

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.782118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 483200ad-ba03-4004-a19e-cae8bf18a7b7 · outbound

This paper cites Interpretation of inaccurate, insufficient and inconsistent data.

Optimal Linear Baseline Models for Scientific Machine Learning Interpretation of inaccurate, insufficient and inconsistent data

Reference 28

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.769809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8c4d53e4-7dc9-4619-871b-2027e65ee37e · outbound

This paper cites An application of the Wiener-Kolmogorov smoothing theory to matrix inversion.

Optimal Linear Baseline Models for Scientific Machine Learning An application of the Wiener-Kolmogorov smoothing theory to matrix inversion

Reference 29

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.758949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation beb0fcb9-615e-4aa6-90ee-5d7891ad4125 · outbound

This paper cites an unresolved cited work.

Optimal Linear Baseline Models for Scientific Machine Learning Unresolved cited work

Reference 30

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.747983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation eacd7c80-258f-45bd-91ae-c9e056795996 · outbound

This paper cites Extrapolation, Interpolation, and Smoothing of Stationary Time Series: with Engi- neering Applications.

Optimal Linear Baseline Models for Scientific Machine Learning Extrapolation, Interpolation, and Smoothing of Stationary Time Series: with Engi- neering Applications

Reference 31

Resolution: malformed identifier; no resolver link, observed 2026-08-05T23:19:28.057543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d00caed-750f-40d0-9f72-eb6522a68c8e · outbound

This paper cites Reduced-Rank Regression for the Multivariate Linear Model.

Optimal Linear Baseline Models for Scientific Machine Learning Reduced-Rank Regression for the Multivariate Linear Model

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.061152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 836d307c-a94b-49d5-b937-c96f5252ae8e · outbound

This paper cites The Bayesian approach to inverse problems.

Optimal Linear Baseline Models for Scientific Machine Learning The Bayesian approach to inverse problems

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.065944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68f95ec2-001f-4662-a565-f4a3311b6265 · outbound

This paper cites Wiley, 2008.

Optimal Linear Baseline Models for Scientific Machine Learning Wiley, 2008

Reference 34

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.709103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 101c45d7-73c1-48bb-a20e-10a8db4fe972 · outbound

This paper cites Inverse problems: a Bayesian perspective.

Optimal Linear Baseline Models for Scientific Machine Learning Inverse problems: a Bayesian perspective

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.074032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b82ec691-dff5-40de-a472-de8de66bed89 · outbound

This paper cites A Paired Autoencoder Framework for Inverse Problems via Bayes Risk Minimization.

Optimal Linear Baseline Models for Scientific Machine Learning A Paired Autoencoder Framework for Inverse Problems via Bayes Risk Minimization

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-08-05T23:19:31.383680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation eb69fa6a-2405-4e39-9b23-862d67c96331 · outbound

This paper cites Paired autoencoders for likelihood-free estimation in inverse problems.

Optimal Linear Baseline Models for Scientific Machine Learning Paired autoencoders for likelihood-free estimation in inverse problems

Reference 37

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.690824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0cf4f883-cbf3-4857-93e2-99b88443c85a · outbound

This paper cites Optimal regularized low rank inverse approximation.

Optimal Linear Baseline Models for Scientific Machine Learning Optimal regularized low rank inverse approximation

Reference 38

Resolution: malformed identifier; no resolver link, observed 2026-08-05T23:19:28.090914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4be519de-8380-4b92-9fba-fa3961a5f01c · outbound

This paper cites Optimal low-rank approximations of Bayesian linear inverse problems.

Optimal Linear Baseline Models for Scientific Machine Learning Optimal low-rank approximations of Bayesian linear inverse problems

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.095122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83a4f853-d4c5-42bb-b106-f77c0b8efe2c · outbound

This paper cites Solving Bayesian inverse problems via variational autoencoders.

Optimal Linear Baseline Models for Scientific Machine Learning Solving Bayesian inverse problems via variational autoencoders

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.099839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1676c104-f904-486b-bc32-604ffcf36ff9 · outbound

This paper cites Why are big data matrices approximately low rank?.

Optimal Linear Baseline Models for Scientific Machine Learning Why are big data matrices approximately low rank?

Reference 41

Resolution: malformed identifier; no resolver link, observed 2026-08-05T23:19:28.104149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ccac2f4-845a-460f-a4f5-443e83480008 · outbound

This paper cites Autoencoders and their applications in machine learning: a survey.

Optimal Linear Baseline Models for Scientific Machine Learning Autoencoders and their applications in machine learning: a survey

Reference 42

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.668576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 38e0cd92-ecb6-4e23-ac5e-942c68ddd9a0 · outbound

This paper cites Medical image denoising using convolutional denoising autoencoders.

Optimal Linear Baseline Models for Scientific Machine Learning Medical image denoising using convolutional denoising autoencoders

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.111328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d42d8ed0-dfce-4d67-bdc7-519ca6db9a6b · outbound

This paper cites Stacked convolutional auto-encoders for hierarchical feature extraction.

Optimal Linear Baseline Models for Scientific Machine Learning Stacked convolutional auto-encoders for hierarchical feature extraction

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.118799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d1b25ea-f59a-4b33-913c-dcd5a257ec47 · outbound

This paper cites Multilayer feedforward networks are uni- versal approximators.

Optimal Linear Baseline Models for Scientific Machine Learning Multilayer feedforward networks are uni- versal approximators

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.122410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67965eb9-86be-4d7e-a15e-cf699fce399d · outbound

This paper cites The mythos of model interpretability: in machine learning, the concept of inter- pretability is both important and slippery.

Optimal Linear Baseline Models for Scientific Machine Learning The mythos of model interpretability: in machine learning, the concept of inter- pretability is both important and slippery

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.126436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51a77e84-bbfa-4c61-93ec-00f16c1fe509 · outbound

This paper cites A survey on neural network interpretability.

Optimal Linear Baseline Models for Scientific Machine Learning A survey on neural network interpretability

Reference 47

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T23:19:31.295501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b84413b8-00dc-4704-9b84-53fb478075e3 · outbound

This paper cites Neural networks and principal component analysis: learning from examples without local minima.

Optimal Linear Baseline Models for Scientific Machine Learning Neural networks and principal component analysis: learning from examples without local minima

Reference 48

Resolution: malformed identifier; no resolver link, observed 2026-08-05T23:19:28.147084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16aa29ed-db8d-4447-88dd-4feeca8aeac6 · outbound

This paper cites Auto-association by multilayer perceptrons and singular value decompo- sition.

Optimal Linear Baseline Models for Scientific Machine Learning Auto-association by multilayer perceptrons and singular value decompo- sition

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.151350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89e16129-af47-477a-876d-bc5261275c64 · outbound

This paper cites From Principal Subspaces to Principal Components with Linear Autoencoders.

Optimal Linear Baseline Models for Scientific Machine Learning From Principal Subspaces to Principal Components with Linear Autoencoders

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.155306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bc95dd9-7285-4770-8a25-51e34d24174f · outbound

This paper cites Regularized linear autoencoders recover the principal components, eventually.

Optimal Linear Baseline Models for Scientific Machine Learning Regularized linear autoencoders recover the principal components, eventually

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.159534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b720d563-3a40-41a9-b4a3-72bbeaa12abc · outbound

This paper cites The approximation of one matrix by another of lower rank.

Optimal Linear Baseline Models for Scientific Machine Learning The approximation of one matrix by another of lower rank

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.163132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1233058e-0b5b-472f-90dc-16103cb3efa7 · outbound

This paper cites Symmetric gauge functions and unitarily invariant norms.

Optimal Linear Baseline Models for Scientific Machine Learning Symmetric gauge functions and unitarily invariant norms

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.166592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f64a5cea-fe61-4e79-8b78-0263a3732e8a · outbound

This paper cites Zur theorie der linearen und nichtlinearen integralgleichungen.

Optimal Linear Baseline Models for Scientific Machine Learning Zur theorie der linearen und nichtlinearen integralgleichungen

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.170790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d984cbbe-c68c-4394-ba5a-00096e422044 · outbound

This paper cites Generalized rank-constrained matrix approximations.

Optimal Linear Baseline Models for Scientific Machine Learning Generalized rank-constrained matrix approximations

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.175207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 306c6905-ab37-4fe2-8496-6e7ca5a8b356 · outbound

This paper cites Finding structure with randomness: probabilistic algo- rithms for constructing approximate matrix decompositions.

Optimal Linear Baseline Models for Scientific Machine Learning Finding structure with randomness: probabilistic algo- rithms for constructing approximate matrix decompositions

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.179248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d38d423d-d345-4866-82c9-0a7703657629 · outbound

This paper cites Near-optimal column-based matrix reconstruction.

Optimal Linear Baseline Models for Scientific Machine Learning Near-optimal column-based matrix reconstruction

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.186489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74742c1e-dab3-41ce-ae82-cc9ae4a254b4 · outbound

This paper cites Dimensionality reduction for k-means clustering and low rank approxi- mation.

Optimal Linear Baseline Models for Scientific Machine Learning Dimensionality reduction for k-means clustering and low rank approxi- mation

Reference 58

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-05T23:19:31.188214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9f2ee133-f96a-4d94-b6e5-b71829c0f036 · outbound

This paper cites Low-rank matrix approximation with manifold regularization.

Optimal Linear Baseline Models for Scientific Machine Learning Low-rank matrix approximation with manifold regularization

Reference 59

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.602524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation faf06b79-b5a4-4509-9a85-28a648b9ab50 · outbound

This paper cites Subspace-orbit randomized decomposi- tion for low-rank matrix approximations.

Optimal Linear Baseline Models for Scientific Machine Learning Subspace-orbit randomized decomposi- tion for low-rank matrix approximations

Reference 60

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-05T23:19:31.010195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ffdbaa11-be0d-42c0-9393-63c16cd2261a · outbound

This paper cites Dimensionality reduction strategy based on auto-encoder.

Optimal Linear Baseline Models for Scientific Machine Learning Dimensionality reduction strategy based on auto-encoder

Reference 61

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-05T23:19:30.748910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9bb3a4ee-3917-4ef2-9c0b-ba5d07554b6f · outbound

This paper cites Rank Reduction Autoencoders.

Optimal Linear Baseline Models for Scientific Machine Learning Rank Reduction Autoencoders

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.207186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3df537d1-afe8-4bcd-ac4c-0950e88c7812 · outbound

This paper cites Learning-based low-rank approximations.

Optimal Linear Baseline Models for Scientific Machine Learning Learning-based low-rank approximations

Reference 63

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-05T23:19:30.541373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ebdc24f5-dc3b-4315-8e9f-db1a67938cb7 · outbound

This paper cites Sparse Bayesian methods for low-rank matrix estimation.

Optimal Linear Baseline Models for Scientific Machine Learning Sparse Bayesian methods for low-rank matrix estimation

Reference 64

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-05T23:19:30.343825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a1476b53-ce2d-4a14-93af-ce0b915bc6b8 · outbound

This paper cites Learning low-rank latent spaces with simple deterministic autoencoder: theoretical and empirical insights.

Optimal Linear Baseline Models for Scientific Machine Learning Learning low-rank latent spaces with simple deterministic autoencoder: theoretical and empirical insights

Reference 65

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-05T23:19:30.149615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation edee38da-8cef-4b26-b8ca-41ecc82f0c8f · outbound

This paper cites Bayes and empirical Bayes methods for data analysis.

Optimal Linear Baseline Models for Scientific Machine Learning Bayes and empirical Bayes methods for data analysis

Reference 66

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.590698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation db191785-201b-4fc8-a3bb-425f8744ba31 · outbound

This paper cites Computing optimal low-rank matrix approximations for image processing.

Optimal Linear Baseline Models for Scientific Machine Learning Computing optimal low-rank matrix approximations for image processing

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.230993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9b26abe-bad2-43dc-921c-45c6fe64ae72 · outbound

This paper cites Optimal regularized inverse matrices for inverse problems.

Optimal Linear Baseline Models for Scientific Machine Learning Optimal regularized inverse matrices for inverse problems

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.241432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36d69015-4f04-4952-bb38-46725af1692a · outbound

This paper cites An efficient approach for computing optimal low-rank regu- larized inverse matrices.

Optimal Linear Baseline Models for Scientific Machine Learning An efficient approach for computing optimal low-rank regu- larized inverse matrices

Reference 69

Resolution: malformed identifier; no resolver link, observed 2026-08-05T23:19:28.246101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88299100-6890-4802-9451-164bbe25dc34 · outbound

This paper cites Auto-Encoding Variational Bayes.

Optimal Linear Baseline Models for Scientific Machine Learning Auto-Encoding Variational Bayes

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.250024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1189294-9b7f-4b7a-9b74-906747bc3f38 · outbound

This paper cites On the reciprocal of the general algebraic matrix.

Optimal Linear Baseline Models for Scientific Machine Learning On the reciprocal of the general algebraic matrix

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.254158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da8be438-505f-47db-a565-33a0baa673ef · outbound

This paper cites A generalized inverse for matrices.

Optimal Linear Baseline Models for Scientific Machine Learning A generalized inverse for matrices

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.257793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7709f85f-57dd-4766-a8ea-c9532302ffb7 · outbound

This paper cites Good Things Come in Pairs: Paired Autoencoders for Inverse Problems.

Optimal Linear Baseline Models for Scientific Machine Learning Good Things Come in Pairs: Paired Autoencoders for Inverse Problems

Reference 73

Resolution: verified exact; local_arxiv, observed 2026-08-05T23:19:29.559480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ba1a2999-3d9c-4c89-97bf-a95b83d07f1c · outbound

This paper cites The Elements of Statistical Learning.

Optimal Linear Baseline Models for Scientific Machine Learning The Elements of Statistical Learning

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.264934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cb23628-acc6-4211-bdb7-e09f19e882d7 · outbound

This paper cites Williams and Carl E.

Optimal Linear Baseline Models for Scientific Machine Learning Williams and Carl E

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.268269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b196d93d-392b-4488-a164-72d054d9b94d · outbound

This paper cites MedMNIST v2-a large-scale lightweight benchmark for 2D and 3D biomedical image classification.

Optimal Linear Baseline Models for Scientific Machine Learning MedMNIST v2-a large-scale lightweight benchmark for 2D and 3D biomedical image classification

Reference 76

Resolution: malformed identifier; no resolver link, observed 2026-08-05T23:19:28.275365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99c55b82-180b-4957-815f-016f50024bfa · outbound

This paper cites Annotated high-throughput mi- croscopy image sets for validation.

Optimal Linear Baseline Models for Scientific Machine Learning Annotated high-throughput mi- croscopy image sets for validation

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.278804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c743a40-7f86-4022-9282-0f0f1479b7c6 · outbound

This paper cites ChestX-ray8: hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases.

Optimal Linear Baseline Models for Scientific Machine Learning ChestX-ray8: hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.282217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60240d76-dcde-4878-9663-f8816cfa5e79 · outbound

This paper cites The Liver Tumor Segmentation Benchmark (LiTS).

Optimal Linear Baseline Models for Scientific Machine Learning The Liver Tumor Segmentation Benchmark (LiTS)

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.286189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a100c4f7-a1f3-4d83-b0be-82d4707d16e4 · outbound

This paper cites an unresolved cited work.

Optimal Linear Baseline Models for Scientific Machine Learning Unresolved cited work

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.271809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 079a8570-46e2-4730-85ba-fede8900a2e1 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Optimal Linear Baseline Models for Scientific Machine Learning Adam: A Method for Stochastic Optimization

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.294967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3feb3e28-5d82-4c42-b002-8b1b59b1edee · outbound

This paper cites Common risk factors in the returns on stocks and bonds.

Optimal Linear Baseline Models for Scientific Machine Learning Common risk factors in the returns on stocks and bonds

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.299144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71028f16-a573-47f3-b6f1-f947b356d77a · outbound

This paper cites Capital asset prices: a theory of market equilibrium under conditions of risk.

Optimal Linear Baseline Models for Scientific Machine Learning Capital asset prices: a theory of market equilibrium under conditions of risk

Reference 83

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-05T23:19:29.518425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 745ec9ec-00c8-4afe-b37c-b6734968751f · outbound

This paper cites The cross-section of expected stock returns.

Optimal Linear Baseline Models for Scientific Machine Learning The cross-section of expected stock returns

Reference 84

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-05T23:19:29.347481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0727322f-567f-43ae-a46e-93e1a6639c05 · outbound

This paper cites Efficient multiple organ localization in CT image using 3D region proposal network.

Optimal Linear Baseline Models for Scientific Machine Learning Efficient multiple organ localization in CT image using 3D region proposal network

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.290347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c1c5ee1-2ce6-4992-a470-143c2763b921 · outbound

This paper cites A cluster driven log-volatility factor model: a deepening on the source of the volatility clustering.

Optimal Linear Baseline Models for Scientific Machine Learning A cluster driven log-volatility factor model: a deepening on the source of the volatility clustering

Reference 86

Resolution: verified exact; local_arxiv, observed 2026-08-05T23:19:29.176360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3801d5eb-3070-4ece-8142-895337c6f232 · outbound

This paper cites The arbitrage theory of capital asset pricing.

Optimal Linear Baseline Models for Scientific Machine Learning The arbitrage theory of capital asset pricing

Reference 87

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.550180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b53df0a7-e382-4353-8ef4-a9f78dc34e92 · outbound

This paper cites yfinance: fownload market data from Yahoo! Finance’s API.

Optimal Linear Baseline Models for Scientific Machine Learning yfinance: fownload market data from Yahoo! Finance’s API

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.323698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc08b810-3cfd-4213-b03b-5a63f8b5beaf · outbound

This paper cites Quant GANs: deep generation of financial time series.

Optimal Linear Baseline Models for Scientific Machine Learning Quant GANs: deep generation of financial time series

Reference 89

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-05T23:19:29.160749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 006b7583-c909-46bd-a62e-eae480887a1b · outbound

This paper cites Principal component analysis.

Optimal Linear Baseline Models for Scientific Machine Learning Principal component analysis

Reference 90

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.561765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 09d263cb-7cb5-43a8-adf8-4d80e1690215 · outbound

This paper cites The Varimax criterion for analytic rotation in factor analysis.

Optimal Linear Baseline Models for Scientific Machine Learning The Varimax criterion for analytic rotation in factor analysis

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.341853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25ae7609-b0c6-41cc-9f86-9b46447b317d · outbound

This paper cites A matrix formulation of Kaiser’s Varimax criterion.

Optimal Linear Baseline Models for Scientific Machine Learning A matrix formulation of Kaiser’s Varimax criterion

Reference 92

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.504043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 533f77ac-e8d4-4dc8-8aa1-2841e3c9b829 · outbound

This paper cites An overview of analytic rotation in exploratory factor analysis.

Optimal Linear Baseline Models for Scientific Machine Learning An overview of analytic rotation in exploratory factor analysis

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.348877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b3bddbd-a09a-441e-b624-e23634d8f9e8 · outbound

This paper cites Fama and Kenneth R.

Optimal Linear Baseline Models for Scientific Machine Learning Fama and Kenneth R

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.352219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55e854a2-06e9-45f3-ae67-f2bb81d953e2 · outbound

This paper cites Campbell, Andrew W.

Optimal Linear Baseline Models for Scientific Machine Learning Campbell, Andrew W

Reference 95

Resolution: verified exact; doi, observed 2026-08-05T23:19:28.529721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1bfdeb18-3e02-4cdf-a401-70db95a48ad1 · outbound

This paper cites Brockwell and Richard A.

Optimal Linear Baseline Models for Scientific Machine Learning Brockwell and Richard A

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.358783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1112bd7e-3579-4d79-9393-07a1b96f02a4 · outbound

This paper cites Generalized autoregressive conditional heteroskedasticity.

Optimal Linear Baseline Models for Scientific Machine Learning Generalized autoregressive conditional heteroskedasticity

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.362774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07672b62-d73d-42ae-a742-650fb96c610a · outbound

This paper cites Unsupervised alignment of embeddings with Wasserstein Procrustes.

Optimal Linear Baseline Models for Scientific Machine Learning Unsupervised alignment of embeddings with Wasserstein Procrustes

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.365950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c794606-57ae-4e88-a80e-59b7d9a9eaf2 · outbound

This paper cites A Mechanism for Producing Aligned Latent Spaces with Autoencoders.

Optimal Linear Baseline Models for Scientific Machine Learning A Mechanism for Producing Aligned Latent Spaces with Autoencoders

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.369000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cceb72f0-7995-479c-b16e-f72f5326335e · outbound

This paper cites A value for n-person games.

Optimal Linear Baseline Models for Scientific Machine Learning A value for n-person games

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.355485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers