Paper Citation Record · LEDGER

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators

As of 15 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 1 inbound Pith citation observation for arXiv:2412.00088.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.00088 v2

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:36:52.894942Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:47:51.822844Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-07T11:47:51.942609Z

Reference resolution

54 of 54 outbound references displayed

verified exact5
verified fuzzy24
unresolved24
parse uncertain1
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4225fce7-4adc-4a52-a6a9-9dfb46c0b09b · outbound

This paper cites Tutorial on amortized optimization, April 2023.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Tutorial on amortized optimization, April 2023

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.698929Z

Source-reported events for the cited work

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Observation 189b80e8-ca52-415c-9312-0afbdcd18a84 · outbound

This paper cites Gradients without Backpropagation.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Gradients without Backpropagation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.703330Z

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Unavailable: canonical work link unavailable.

Observation 0ab1ba34-442f-44bd-8106-a879359e975a · outbound

This paper cites Deep splitting method for parabolic PDEs.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Deep splitting method for parabolic PDEs

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-12T11:36:53.121301Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fc545036-8e89-4663-b963-e1e97e68a176 · outbound

This paper cites Numerical simulations for full history recursive multilevel Picard approximations for systems of high-dimensional partial differential equations.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Numerical simulations for full history recursive multilevel Picard approximations for systems of high-dimensional partial differential equations

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.711223Z

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Observation 5cc3add9-ae50-4179-8e10-018a336ebdfd · outbound

This paper cites Tadiff , a flexible c + + package for automatic differentiation using taylor series expansion.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Tadiff , a flexible c + + package for automatic differentiation using taylor series expansion

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.527614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f31f7b76-bb77-4a88-96cc-c215060eabce · outbound

This paper cites Johnson, and David Duvenaud.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Johnson, and David Duvenaud

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.517392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 41cd22c9-b263-417c-b029-9b70587720d9 · outbound

This paper cites JAX: composable transformations of Python+NumPy programs, 2018.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators JAX: composable transformations of Python+NumPy programs, 2018

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.722551Z

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Observation 92ae3bb4-f65b-4b66-bdf0-feb258a3c686 · outbound

This paper cites Johnson-Lindenstrauss Lemma, Linear and Nonlinear Random Projections, Random Fourier Features, and Random Kitchen Sinks: Tutorial and Survey.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Johnson-Lindenstrauss Lemma, Linear and Nonlinear Random Projections, Random Fourier Features, and Random Kitchen Sinks: Tutorial and Survey

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.725872Z

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Observation 820a11a1-6291-4d85-9ed9-d68323f3ae3d · outbound

This paper cites Evaluating Derivatives.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Evaluating Derivatives

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.499865Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2a57c7ca-e776-4c67-b89f-8864d4f21533 · outbound

This paper cites Solving high-dimensional partial differential equations using deep learning.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Solving high-dimensional partial differential equations using deep learning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.489192Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6115110e-2229-4db4-aa0b-e25868151068 · outbound

This paper cites Learning Physics-Informed Neural Networks without Stacked Back-propagation, February.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Learning Physics-Informed Neural Networks without Stacked Back-propagation, February

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.477866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e49ec4b0-da5a-4205-9160-ab68b70ad542 · outbound

This paper cites Hutchinson Trace Estimation for High-Dimensional and High-Order Physics-Informed Neural Networks.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Hutchinson Trace Estimation for High-Dimensional and High-Order Physics-Informed Neural Networks

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-12T11:36:53.076249Z

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Observation 0c21c2c3-203b-48dd-a887-3d0e61443149 · outbound

This paper cites Tackling the curse of dimensionality with physics-informed neural networks.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Tackling the curse of dimensionality with physics-informed neural networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.748314Z

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Observation 0d413ed3-36ea-4b5f-9819-422c9f830d27 · outbound

This paper cites Bias-Variance Trade-off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Bias-Variance Trade-off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.751355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a122d382-766a-4b94-bad7-0e37cb1c3139 · outbound

This paper cites Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations, February.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations, February

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.461050Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5d04e661-72f5-4fcc-a5c9-0212d2391ba4 · outbound

This paper cites Hutchinson.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Hutchinson

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.450455Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6cd110c3-9813-4066-b131-fe98fae39278 · outbound

This paper cites Overcoming the curse of dimensionality in the numerical approximation of semilinear parabolic partial differential equations, July 2018.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Overcoming the curse of dimensionality in the numerical approximation of semilinear parabolic partial differential equations, July 2018

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.439149Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9ba67f3b-b38c-4ba4-8a8b-e4ed38c36516 · outbound

This paper cites Functional differentiation of computer programs.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Functional differentiation of computer programs

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.427884Z

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Observation 57125dce-76e5-4cbb-83be-83ea2e70e140 · outbound

This paper cites Kevrekidis, Lu Lu, Paris Perdikaris, Sifan Wang, and Liu Yang.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Kevrekidis, Lu Lu, Paris Perdikaris, Sifan Wang, and Liu Yang

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.416785Z

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Observation 7510ed7a-f30f-48af-abbf-111be903c703 · outbound

This paper cites Kingma and Jimmy Ba.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Kingma and Jimmy Ba

Reference 20

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Observation 762f9405-45e9-4389-a435-21e1c7f74d66 · outbound

This paper cites Regularizing score-based models with score fokker-planck equations.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Regularizing score-based models with score fokker-planck equations

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.400408Z

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Observation 9626cb03-29b1-4048-a063-e11a80747607 · outbound

This paper cites A general construction for abstract interpretation of higher-order automatic differentiation.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators A general construction for abstract interpretation of higher-order automatic differentiation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.389333Z

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Observation c6072b62-47dd-4e19-b9f4-3ca9adad09fe · outbound

This paper cites DOF: Accelerating high-order differential operators with forward propagation.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators DOF: Accelerating high-order differential operators with forward propagation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.378792Z

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Observation a41a1e91-a36a-4799-9dc8-614ebf183872 · outbound

This paper cites Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo

Reference 24

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Observation 585a529e-a13c-4ef0-a4d1-4b2f20599f9d · outbound

This paper cites A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-12T11:36:53.033258Z

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Observation 2f10e7dd-12f4-4051-af88-2db89b292ac0 · outbound

This paper cites an unresolved cited work.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Unresolved cited work

Reference 26

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Observation 83d5a2ec-620d-486f-81f6-195af41fbf09 · outbound

This paper cites Fine-Tuning Language Models with Just Forward Passes.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Fine-Tuning Language Models with Just Forward Passes

Reference 27

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Observation d74e5895-7605-4419-977c-917f1ed0208f · outbound

This paper cites Randomized Numerical Linear Algebra: Foundations & Algorithms.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Randomized Numerical Linear Algebra: Foundations & Algorithms

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.804026Z

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Observation f0f0036b-1aed-47d6-a83f-aa59bd9b2208 · outbound

This paper cites Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.807810Z

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Observation 5ee6dbcf-5932-4c14-bf7f-db0218421e86 · outbound

This paper cites Randomized Automatic Differentiation.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Randomized Automatic Differentiation

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-12T11:36:52.991643Z

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Observation 1d3df6b3-62d6-470e-a7bd-7429c191b054 · outbound

This paper cites Efficient Learning of Generative Models via Finite-Difference Score Matching.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Efficient Learning of Generative Models via Finite-Difference Score Matching

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.815859Z

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Observation b8d3a40f-934c-48b1-a549-c792f9660da2 · outbound

This paper cites Lax pairs informed neural networks solving integrable systems.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Lax pairs informed neural networks solving integrable systems

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.819962Z

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Observation 471e95b8-c668-49e7-9783-281d0a2ee3e0 · outbound

This paper cites Raissi, P.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Raissi, P

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.360437Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4ed8e355-5a1c-41d2-a5b9-0458a3554aea · outbound

This paper cites Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.827729Z

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Observation d9b647db-9130-4cc6-94f4-d0910eb9395e · outbound

This paper cites Dgm: a deep learning algorithm for solving partial differential equations.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Dgm: a deep learning algorithm for solving partial differential equations

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.350463Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 008b33ab-73c7-4df3-99bf-f903ccc77a93 · outbound

This paper cites Modern analysis of hutchinson’s trace estimator.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Modern analysis of hutchinson’s trace estimator

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.339648Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 08777bf8-d88b-47bc-bc9f-516c47e2eebf · outbound

This paper cites Sliced Score Matching: A Scalable Approach to Density and Score Estimation.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Sliced Score Matching: A Scalable Approach to Density and Score Estimation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.840685Z

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Observation 55217750-5c04-439b-a580-63d29aaa88e8 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Score-Based Generative Modeling through Stochastic Differential Equations

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.844614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7df35c89-a4f4-453a-b3be-b01b2a5a0eea · outbound

This paper cites an unresolved cited work.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-12T11:36:53.329500Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5433034a-b05a-4045-95c2-d469fb195e13 · outbound

This paper cites High Order Reverse Mode of Automatic Differentiation.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators High Order Reverse Mode of Automatic Differentiation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.319522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d959bf13-6063-45d5-a98d-fa4e0248b706 · outbound

This paper cites The deep ritz method: a deep learning-based numerical algorithm for solving variational problems.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators The deep ritz method: a deep learning-based numerical algorithm for solving variational problems

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.308685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6bd6a628-4814-4e72-9bc6-8de5ee3b23fb · outbound

This paper cites Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.859086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5894fe3a-cdac-4cdb-a2a5-41bb69ca7f16 · outbound

This paper cites Weak Adversarial Networks for High-dimensional Partial Differential Equations.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Weak Adversarial Networks for High-dimensional Partial Differential Equations

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.862725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f31d147-1dc8-44a2-859e-7d1cf720a91c · outbound

This paper cites an unresolved cited work.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Unresolved cited work

Reference 46

Resolution: unresolved; raw_fallback, observed 2026-08-12T11:36:53.298053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7834d975-d468-4326-b845-334cd82a5541 · outbound

This paper cites , jT ) where v(j) = 0 when j ̸∈ J and jt < kfor all t ∈ [1, T], such that when setting pj = 0, j ̸∈ J qit , j = jt , (54) (p1, p2,.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators , jT ) where v(j) = 0 when j ̸∈ J and jt < kfor all t ∈ [1, T], such that when setting pj = 0, j ̸∈ J qit , j = jt , (54) (p1, p2,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.287722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bafc7a29-9e0d-44c0-a7a5-accdc8f1fc1d · outbound

This paper cites off-diagonalness.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators off-diagonalness

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.276973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ec6c12a7-09e3-4b7f-a8c9-fb6b485c36e2 · outbound

This paper cites Stacked Backward mode SDGD in JAX.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Stacked Backward mode SDGD in JAX

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.266425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9e1e00f4-d356-4fa6-bf93-327c30012c5c · outbound

This paper cites an unresolved cited work.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Unresolved cited work

Reference 50

Resolution: unresolved; raw_fallback, observed 2026-08-12T11:36:53.255263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 78b4b1c1-1c11-453f-924d-34c831b619d9 · outbound

This paper cites (67) which can be expanded as utx + 6uxux + 6uuxx + uxxxx + 3σ2uyy = 0.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators (67) which can be expanded as utx + 6uxux + 6uuxx + uxxxx + 3σ2uyy = 0

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.245649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a380ad8e-d7aa-4d13-a9ae-71ac30cb693e · outbound

This paper cites (71) Gradient-enhanced PINN (gPINN) [42] regularizes the learned PINN such that the gradient of the residual is close to the zero vector.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators (71) Gradient-enhanced PINN (gPINN) [42] regularizes the learned PINN such that the gradient of the residual is close to the zero vector

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.235668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8f3d7b5d-df9f-4da3-a9fa-3ab8016d92f3 · outbound

This paper cites an unresolved cited work.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Unresolved cited work

Reference 53

Resolution: parse uncertain; raw_fallback, observed 2026-08-12T11:36:53.225233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 36b2b604-cea0-4711-8693-1ce2e83bbe1f · outbound

This paper cites None” in the “gPINN method.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators None” in the “gPINN method

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:36:53.214638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e8cbe8dc-581f-4c71-8de6-491482505ed2 · outbound

This paper cites Learning Physics-Informed Neural Networks without Stacked Back-propagation.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Learning Physics-Informed Neural Networks without Stacked Back-propagation

Reference 2023

Resolution: verified exact; local_arxiv, observed 2026-08-12T11:36:53.090059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 48993566-5c23-4dca-8bdd-5ef6872259c5 · outbound

This paper cites Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations.

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-12T11:36:52.758699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation fbd01193-e5c0-4248-8811-7aef4b5dc84c · inbound

PMNO: A novel physics guided multi-step neural operator predictor for partial differential equations cites this paper.

PMNO: A novel physics guided multi-step neural operator predictor for partial differential equations Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators

Reference 64

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:47:51.987662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.