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Paper Citation Record · LEDGER

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations

As of 7 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 2 inbound Pith citation observations for arXiv:2508.03839.

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

pith.paper-citation-record.v1
2508.03839 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:14:00.311134Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:16:27.970183Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T14:39:58.504186Z

Reference resolution

68 of 68 outbound references displayed

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External citation measurements

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Outbound references

Observation 035d2a00-97e3-40a5-8f88-4c69d2825245 · outbound

This paper cites Springer, 2003.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Springer, 2003

Reference 1

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Source-reported events for the cited work

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Observation a887bd5d-d6df-4ca2-9953-7b157ebd7cd8 · outbound

This paper cites Efficient Concentration with Gaussian Approximation.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Efficient Concentration with Gaussian Approximation

Reference 2

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Observation db4e463d-7ec3-4516-bd7f-8c43c15e41f2 · outbound

This paper cites Change-point analysis in financial networks.Stat, 9(1):e269, 2020.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Change-point analysis in financial networks.Stat, 9(1):e269, 2020

Reference 3

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Observation 66cc3a71-eced-407a-b219-07864abf96ff · outbound

This paper cites Koml´ os–Major–Tusn´ ady approximation under dependence.The Annals of Probability, 42(2):794–817, 2014.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Koml´ os–Major–Tusn´ ady approximation under dependence.The Annals of Probability, 42(2):794–817, 2014

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation a30b39e5-001e-4628-95b0-e82e4be568bb · outbound

This paper cites On strong embeddings by Stein’s method.Electronic Journal of Probability, 21(none):1 – 30, 2016.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations On strong embeddings by Stein’s method.Electronic Journal of Probability, 21(none):1 – 30, 2016

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation f70940d5-8d9d-4019-b65d-8c563594cf17 · outbound

This paper cites an unresolved cited work.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Unresolved cited work

Reference 6

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Observation faf5410d-9e89-4019-94a8-b9eae164168b · outbound

This paper cites Rates in the Central Limit Theorem and diffusion approximation via Stein's Method.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Rates in the Central Limit Theorem and diffusion approximation via Stein's Method

Reference 7

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Source-reported events for the cited work

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Observation f7e03bb8-7712-4924-8b7d-f30e6fcb3637 · outbound

This paper cites an unresolved cited work.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Unresolved cited work

Reference 8

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Observation 33b51a8e-c4cb-47d8-9733-88a163d3149b · outbound

This paper cites Improved rates of convergence for the multivariate Central Limit Theorem in Wasserstein distance.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Improved rates of convergence for the multivariate Central Limit Theorem in Wasserstein distance

Reference 9

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Source-reported events for the cited work

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Observation a2d3a202-9cdb-4ad8-ab83-0b4a25409271 · outbound

This paper cites Automatic change detection in multimodal serial MRI: application to multiple sclerosis lesion evolution.NeuroImage, 20(2):643–656, 2003.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Automatic change detection in multimodal serial MRI: application to multiple sclerosis lesion evolution.NeuroImage, 20(2):643–656, 2003

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 04d9a0ad-0507-44b5-bfcb-c45d03aa3482 · outbound

This paper cites Simulation of Brownian motion at first-passage times.Math- ematics and Computers in Simulation, 77(1):64–71, 2008.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Simulation of Brownian motion at first-passage times.Math- ematics and Computers in Simulation, 77(1):64–71, 2008

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation d7b8d712-8d5d-4b77-a343-1f97ccf84e30 · outbound

This paper cites Bounds on the running maximum of a random walk with small drift.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Bounds on the running maximum of a random walk with small drift

Reference 12

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Source-reported events for the cited work

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Observation c6867601-1302-43d1-8cf6-33bfc27f0df1 · outbound

This paper cites Strong approximations of bivariate uniform empirical processes.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Strong approximations of bivariate uniform empirical processes

Reference 13

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Source-reported events for the cited work

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Observation 141ad869-3a93-43a2-aab4-21adab9567e4 · outbound

This paper cites A new approach to strong embeddings.Probability Theory and Related Fields, 152(1-2):231–264, 2012.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations A new approach to strong embeddings.Probability Theory and Related Fields, 152(1-2):231–264, 2012

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation cb37c1e9-4096-4cc0-b497-2b25ad86dd15 · outbound

This paper cites Inference of breakpoints in high-dimensional time series.Journal of the American Statistical Association, 117(540):1951–1963, 2022.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Inference of breakpoints in high-dimensional time series.Journal of the American Statistical Association, 117(540):1951–1963, 2022

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 9f546998-01f8-4bea-b801-f07bc5c19180 · outbound

This paper cites From stein identities to moderate deviations.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations From stein identities to moderate deviations

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 6cee9a47-9d12-447e-9164-7ccfeeb065bf · outbound

This paper cites Some applications of first-passage ideas to finance, 2013.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Some applications of first-passage ideas to finance, 2013

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:55.078165Z digest=sha256:72d4d87f1ac27b25f383464cfd1564fe31fdba103b3e8de9270db79ae986e34a

Observation 6c60221e-41bb-42eb-be0e-3abe3413c000 · outbound

This paper cites Sharp bounds on the absolute moments of a sum of two iid random variables.The Annals of Probability, pages 765–771, 1983.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Sharp bounds on the absolute moments of a sum of two iid random variables.The Annals of Probability, pages 765–771, 1983

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation e5afcefc-ff23-4cd0-99a3-20c5b7019665 · outbound

This paper cites Sur un nouveau th´ eoreme-limite de la th´ eorie des probabilit´ es.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Sur un nouveau th´ eoreme-limite de la th´ eorie des probabilit´ es

Reference 19

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 8872d15d-11fb-497d-86fb-5cf605ec117d · outbound

This paper cites Simulation of first-passage times for alternating Brownian motions.Methodology and Computing in Applied Probability, 7(2):161–181, 2005.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Simulation of first-passage times for alternating Brownian motions.Methodology and Computing in Applied Probability, 7(2):161–181, 2005

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 8450e642-9d89-49af-8d77-344fff0863bd · outbound

This paper cites Bounds for the absolute third moment.Scandinavian Journal of Statistics, pages 149–152, 1975.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Bounds for the absolute third moment.Scandinavian Journal of Statistics, pages 149–152, 1975

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation bd6e6dda-40d3-48be-955d-639ec8e8d64d · outbound

This paper cites Fromp-wasserstein bounds to moderate deviations.Electronic Journal of Probability, 28:1–52, 2023.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Fromp-wasserstein bounds to moderate deviations.Electronic Journal of Probability, 28:1–52, 2023

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 72bc6932-1bc1-410a-b93e-4384b1e8e10f · outbound

This paper cites Retracted chapter: Generalization of a probability limit theorem of cram´ er.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Retracted chapter: Generalization of a probability limit theorem of cram´ er

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 5250e35d-369b-40a6-95e3-a47bc67f0863 · outbound

This paper cites Multiscale change point inference.Journal of the Royal Statistical Society Series B: Statistical Methodology, 76(3):495–580, 2014.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Multiscale change point inference.Journal of the Royal Statistical Society Series B: Statistical Methodology, 76(3):495–580, 2014

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 281d7f57-acb1-49d4-aaf0-5f683570f918 · outbound

This paper cites Random walk models for the spike activity of a single neuron.Biophysical journal, 4(1):41–68, 1964.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Random walk models for the spike activity of a single neuron.Biophysical journal, 4(1):41–68, 1964

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 17fa2e4e-61ff-4959-bac9-25368df64268 · outbound

This paper cites Cambridge University Press, 2014.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Cambridge University Press, 2014

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:55.905263Z digest=sha256:d5c6b45d0eea9a7339acd4c54a9d949bcd13f7fb8fb5930e07b88c026855c1db

Observation 63ee4565-67a7-4075-a758-1fde8378b3ed · outbound

This paper cites Bayesian online change point detection in finance.Financial Internet Quarterly, 17(4):27–33, 2021.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Bayesian online change point detection in finance.Financial Internet Quarterly, 17(4):27–33, 2021

Reference 27

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raw_fallback, observed 2026-08-06T04:14:06.034388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation d334ae87-3335-420e-b00a-5a0bd147f76f · outbound

This paper cites Springer Science & Business Media, 2012.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Springer Science & Business Media, 2012

Reference 28

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raw_fallback, observed 2026-08-06T04:14:05.913318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation f38df772-b2fd-4b12-8bf4-d597aca72ba8 · outbound

This paper cites Courier Corporation, 2012.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Courier Corporation, 2012

Reference 29

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raw_fallback, observed 2026-08-06T04:14:05.653062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:56.239112Z digest=sha256:347b71424ac1476c9ea85660131f02f9f87f46d8eaaa46328e3ac6582b98d21e

Observation a959bf94-d3a9-4304-8d3c-28e3c237a8d8 · outbound

This paper cites Self-normalized cram´ er-type large deviations for independent random variables.The Annals of probability, 31(4):2167–2215, 2003.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Self-normalized cram´ er-type large deviations for independent random variables.The Annals of probability, 31(4):2167–2215, 2003

Reference 30

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raw_fallback, observed 2026-08-06T04:14:05.412332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 107d4fd7-50a0-456a-bc50-443756970a69 · outbound

This paper cites Springer Science & Business Media, 2012.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Springer Science & Business Media, 2012

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-06T04:14:05.167144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:56.410303Z digest=sha256:228cc37556bbe5717936cf93690f65e4a94b1fca5ffad1dc41aa24c34d76398a

Observation 4bb65565-7292-4e14-b78f-1c1eced83855 · outbound

This paper cites Dynkin ′ s Games and Israeli Options.International Scholarly Research Notices, 2013(1):856458, 2013.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Dynkin ′ s Games and Israeli Options.International Scholarly Research Notices, 2013(1):856458, 2013

Reference 32

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raw_fallback, observed 2026-08-06T04:14:04.881239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:56.500134Z digest=sha256:07b955769955cac4f46033eaa4a2cabc9c479370c604263285d67ca0221466f7

Observation ab379614-7db5-465a-b7b4-98cd65f755d1 · outbound

This paper cites An approximation of partial sums of independent R V’-s, and the sample DF.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations An approximation of partial sums of independent R V’-s, and the sample DF

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:04.594436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:56.560958Z digest=sha256:0434c34f5a620208e6c7ccd068d8221906bac80146019e93db6f5d8bf6cc112a

Observation 5d9320c4-ac1a-4dae-b34c-892fb86b9da9 · outbound

This paper cites An approximation of partial sums of independent R V’s, and the sample DF.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations An approximation of partial sums of independent R V’s, and the sample DF

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:04.355424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:56.699640Z digest=sha256:76ee1651f1ba3e77b03606eab8e1baea38ca7b717dab339302cee732ac838c68

Observation 666ac376-e542-4b52-a29d-9b5d08d132e4 · outbound

This paper cites A jump-diffusion model for option pricing.Management science, 48(8):1086–1101, 2002.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations A jump-diffusion model for option pricing.Management science, 48(8):1086–1101, 2002

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:04.204870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:56.828678Z digest=sha256:e35ddb3e773819a3ee60996111082d2d92b93e7de8ffc81c15a49abd4018d1ff

Observation 9033b867-ea47-4211-9ad9-cda6be258130 · outbound

This paper cites First exit time of a random walk from the boundsf(n)±cg(n), with applications.The Annals of Probability, 7(4):672–692, 1979.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations First exit time of a random walk from the boundsf(n)±cg(n), with applications.The Annals of Probability, 7(4):672–692, 1979

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:04.066431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:56.909865Z digest=sha256:5b6f5e15a052aaf0bff59d329b718f7093ec6c52deb6f3a5b1478581055616d8

Observation 33e33659-b0d7-4d67-815b-ebf9b761f018 · outbound

This paper cites Optimal stopping and embedding.Journal of applied probability, 37(4):1143–1148, 2000.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Optimal stopping and embedding.Journal of applied probability, 37(4):1143–1148, 2000

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:03.985137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:57.001334Z digest=sha256:7e1894516826f72de34eef01c92b2456a4f28876fc8aa7ba544ccd3e1b19dfe2

Observation 8e1c2302-9d37-469a-be96-50dc3d037396 · outbound

This paper cites Habilitation ` a diriger des recherches, Universit´ e de Lille Nord de France, February 2019.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Habilitation ` a diriger des recherches, Universit´ e de Lille Nord de France, February 2019

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:03.922744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:57.083495Z digest=sha256:1e43c5c16925bd29b9027817b0aa4a065bf6faa73ea4fc9a1b26c284ad7317b0

Observation 0a65937c-db69-42b3-b862-a672beed37df · outbound

This paper cites The approximation of partial sums of independent rv’s.Zeitschrift f¨ ur Wahrschein- lichkeitstheorie und verwandte Gebiete, 35(3):213–220, 1976.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations The approximation of partial sums of independent rv’s.Zeitschrift f¨ ur Wahrschein- lichkeitstheorie und verwandte Gebiete, 35(3):213–220, 1976

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:03.784356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:57.175814Z digest=sha256:b12b02755cb24f85f8e80d4735611b36899c2b79f970b2d0678058c567d8a4ee

Observation 9a1184a9-3483-4fff-89df-85e2baa4c18a · outbound

This paper cites Online Bayesian change point detection algorithms for segmentation of epileptic activity.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Online Bayesian change point detection algorithms for segmentation of epileptic activity

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:03.623953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:57.324066Z digest=sha256:e6ad4d58a6429eabb16a3be6541b16083bda0c5d7dec7e885f296a2b31c90bde

Observation a1eafe7b-ad71-4322-a4a3-9a1b8d7373df · outbound

This paper cites Sharp Empirical Bernstein Bounds for the Variance of Bounded Random Variables.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Sharp Empirical Bernstein Bounds for the Variance of Bounded Random Variables

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:57.429821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:57.429821Z digest=sha256:cad8bde89290d3668be7983190e34162abcfc39861f00b67f107af85754155e2

Observation e99e1c0a-f8ac-43a0-8e4c-0a7b55d2562c · outbound

This paper cites Quantile coupling inequalities and their applications.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Quantile coupling inequalities and their applications

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:57.506463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:57.506463Z digest=sha256:3d852bd341c2f218cb8ea3c31f6ecd713d64fef25cfc5fd7a4aeaa68ed55c7e0

Observation 410bd02b-15bd-42ce-8613-0c38b7a967cb · outbound

This paper cites Sequential Gaussian approximation for nonstationary time series in high dimensions.Bernoulli, 29(4):3114–3140, 2023.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Sequential Gaussian approximation for nonstationary time series in high dimensions.Bernoulli, 29(4):3114–3140, 2023

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:03.462574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:57.598769Z digest=sha256:53f4b7a602db8aa8501506008b2811b514a0bf7afba7df01b62c1007ef06d4a9

Observation 4e8861b8-62b2-4c3c-8cf7-930a59b59c9e · outbound

This paper cites John wiley & sons, 2020.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations John wiley & sons, 2020

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:57.674936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:57.674936Z digest=sha256:41bcea9402567d965735a19684ef2849f28cc4e1ab5a495d9c9c3f4c624109ef

Observation 6f7e00c7-53ac-4b6c-82d9-c40c29a10b97 · outbound

This paper cites Some inequalities for the distribution of sums of independent random variables.Theory of Probability & Its Applications, 22(2):248–256, 1978.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Some inequalities for the distribution of sums of independent random variables.Theory of Probability & Its Applications, 22(2):248–256, 1978

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:03.316872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:57.774267Z digest=sha256:4eba8f7fa435d82ee80eeda26d35b956d6819412161bf94a09cbfa631e806c6a

Observation e7837efc-f6fc-4dbc-9683-46f48b4d76ef · outbound

This paper cites Asymptotic equivalence of density estimation and Gaussian white noise.The Annals of Statistics, pages 2399–2430, 1996.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Asymptotic equivalence of density estimation and Gaussian white noise.The Annals of Statistics, pages 2399–2430, 1996

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:03.149872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:57.863950Z digest=sha256:121b20b125c17f8987c50490a50b0e73de11ac84b95cdbbc77f1f61a8a00260e

Observation e670e80c-ab41-4661-8c75-3dd7d5d6c848 · outbound

This paper cites A note on Burkholder-Rosenthal inequality.Bull.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations A note on Burkholder-Rosenthal inequality.Bull

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:03.019049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:57.992536Z digest=sha256:e002bb92cccecae6c1e1e1a642963bcbd52398004a3e69671cf2109107601452

Observation 8409fde2-e3a6-466a-b0dc-8f9ac1b26a78 · outbound

This paper cites Generalization of an inequality by Talagrand and links with the logarithmic Sobolev inequality.Journal of Functional Analysis, 173(2):361–400, 2000.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Generalization of an inequality by Talagrand and links with the logarithmic Sobolev inequality.Journal of Functional Analysis, 173(2):361–400, 2000

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:58.094377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:58.094377Z digest=sha256:2116992c7701d1d6a98f329eeab0615bc3cbb90f561c9e1e75f910c71fef123d

Observation f7bad74b-82f4-4150-8407-441d828114cd · outbound

This paper cites Continuous inspection schemes.Biometrika, 41(1/2):100–115, 1954.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Continuous inspection schemes.Biometrika, 41(1/2):100–115, 1954

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:58.213243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:58.213243Z digest=sha256:dd196a8336f245dda7dfe4707e401e30f5915efe9a444974e4c29b15327abab5

Observation 83678556-6b02-4979-9c23-8a0822ba7ef9 · outbound

This paper cites an unresolved cited work.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-06T04:14:02.864972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:58.320830Z digest=sha256:a0ee6c5b8346f688d4be1576938a4d7c897a25f9c9ba6eba45e5de5429bbc19e

Observation 36cf916b-4786-4b34-83a2-7540daed40af · outbound

This paper cites Springer Science & Business Media, 2012.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Springer Science & Business Media, 2012

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:58.394383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:58.394383Z digest=sha256:42105d33a9828413e1cd2ec11193b429398654bef6879e401fd524ea09e3714a

Observation 1a6a9894-aacd-4ab3-b411-a51762c5d947 · outbound

This paper cites Probability bounds for first exits through moving boundaries.The Annals of Probability, pages 106–117, 1978.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Probability bounds for first exits through moving boundaries.The Annals of Probability, pages 106–117, 1978

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:02.731837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:58.477953Z digest=sha256:dfe4727917653991e8e65c928fa75e2f2e39bca7af2e71486037ef91d39136d5

Observation d902829b-1f90-4251-8731-daecbe2ac58a · outbound

This paper cites John Wiley & Sons, 2003.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations John Wiley & Sons, 2003

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:58.600742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:58.600742Z digest=sha256:3678b073044523ac6d682ecd0703347a50e06629baa1afbf5133a092fb0784c7

Observation fbba294c-9a17-4a10-95dc-519494f253d0 · outbound

This paper cites Moment inequalities for sums of dependent random variables under projective conditions.Journal of Theoretical Probability, 22(1):146–163, 2009.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Moment inequalities for sums of dependent random variables under projective conditions.Journal of Theoretical Probability, 22(1):146–163, 2009

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:02.543459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:58.701407Z digest=sha256:60ae397552aadbd05dacc1bc9431ecea9d34451b3b635b4d2093beb967ea82f0

Observation ee767303-ae64-46d0-9b3f-6111a4ff2f97 · outbound

This paper cites A remark on Stirling’s formula.The American mathematical monthly, 62(1):26– 29, 1955.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations A remark on Stirling’s formula.The American mathematical monthly, 62(1):26– 29, 1955

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:02.431458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:58.807444Z digest=sha256:1d044a2824882f20b9dc24d8f1f890e1284f7b267c76d5c94426722b1106f5ba

Observation b49ba4db-37ee-4b0e-9738-5f8695d70dc3 · outbound

This paper cites On the accuracy of normal approximation in the invariance principle.Matematicheskie Trudy, 13:40–66, 1989.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations On the accuracy of normal approximation in the invariance principle.Matematicheskie Trudy, 13:40–66, 1989

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:02.307086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:58.872156Z digest=sha256:f8166e6d8294544826a74e213e51e573c2cdb6b2fd8a52c5f9bfab860057b10d

Observation f53c2363-5a2b-4853-b0e9-762683941240 · outbound

This paper cites Reducing sequential change detection to sequential estimation.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Reducing sequential change detection to sequential estimation

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:58.981514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:58.981514Z digest=sha256:47cdae1daab2aa0832389666c81fbe000a8b9728b3d4240c7564ca81a7672025

Observation 0d5e04ac-6ce0-4ba8-873f-78531c463f10 · outbound

This paper cites Springer, 2004.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Springer, 2004

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:02.179908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:59.021374Z digest=sha256:e112dddf349f5c96bda485f18722fa9700cbf134e7c7c64211b888511fcfa36a

Observation 3789902b-67ec-445e-824b-04d7b4d1ccae · outbound

This paper cites Staudacher, S.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Staudacher, S

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:02.023185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:59.098287Z digest=sha256:bcce8fd6c600e8c109fb1e2353381592e2874142cce362838fbce469669e3309

Observation d3723309-ad58-4df3-b4ea-0ed5a0b92b5e · outbound

This paper cites John Wiley & Sons, 2001.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations John Wiley & Sons, 2001

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:01.844851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:59.224312Z digest=sha256:585edc9fc4fe291ab65e6f4dd3c5f1418141f4bc6b9bb80cff7aec0696f72599

Observation 96a77237-fb32-45ed-8ebd-a93bdd308137 · outbound

This paper cites Survival Multiarmed Bandits with Bootstrapping Methods.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Survival Multiarmed Bandits with Bootstrapping Methods

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:59.361814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:59.361814Z digest=sha256:271019fdd8a5777478c4041bd67c36da541d82f746b38cc5c8d78edcf9b5ac09

Observation 6492fea4-946c-4db1-951a-12adfa72ba3b · outbound

This paper cites American Mathematical Soc., 2003.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations American Mathematical Soc., 2003

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:59.504338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:59.504338Z digest=sha256:4aca61b4ef7b141bc19f0a807693c10a24faccec49fe1847702c1bad1353bddc

Observation d3d0d7f1-23ca-48b2-9cb3-0cbb18000cf8 · outbound

This paper cites The rate of convergence of the binomial tree scheme.Finance and Stochastics, 7(3):337–361, 2003.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations The rate of convergence of the binomial tree scheme.Finance and Stochastics, 7(3):337–361, 2003

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:01.706865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T04:13:59.652498Z digest=sha256:8065ea05116351d6fbfefa65fa6ea13858eda9896c8894c5ff0e8f5ccf3b3857

Observation 0351c1d8-c5ea-40a5-a1b0-40aa8ea9ca0d · outbound

This paper cites Distribution-uniform anytime- valid sequential inference.arXiv preprint arXiv:2311.03343, 2023.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Distribution-uniform anytime- valid sequential inference.arXiv preprint arXiv:2311.03343, 2023

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:59.737737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:59.737737Z digest=sha256:3d309cca6867e3f0bc361cd2b6ae11e24c645cd75165c94bede98baad37f0717

Observation 10a38bf1-0170-4fb0-941f-b132844931e6 · outbound

This paper cites Nonasymptotic and distribution- uniform Koml´ os–Major–Tusn´ ady approximation.arXiv preprint arXiv:2502.06188, 2025.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Nonasymptotic and distribution- uniform Koml´ os–Major–Tusn´ ady approximation.arXiv preprint arXiv:2502.06188, 2025

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:59.891409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:59.891409Z digest=sha256:e26fe8b1158d22353d4a7b86b97862fb555fd65e78cfe0e46fbcfda5079c0f09

Observation b0987185-aed1-4c4c-9682-fae9f95f51fc · outbound

This paper cites Estimating means of bounded random variables by betting.Journal of the Royal Statistical Society Series B: Statistical Methodology, 86(1):1–27, 2024.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Estimating means of bounded random variables by betting.Journal of the Royal Statistical Society Series B: Statistical Methodology, 86(1):1–27, 2024

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:01.537492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 4b82fc2f-b6aa-438e-a050-ec752c0d3720 · outbound

This paper cites Some current directions in the theory and application of statistical process monitoring.Journal of quality technology, 46(1):78–94, 2014.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Some current directions in the theory and application of statistical process monitoring.Journal of quality technology, 46(1):78–94, 2014

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:01.287813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 5386f057-cd97-4d95-9e1e-84a90876b992 · outbound

This paper cites Adaptive change detection in heart rate trend monitoring in anesthetized children.IEEE transactions on biomedical engineering, 53(11):2211–2219, 2006.

VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Adaptive change detection in heart rate trend monitoring in anesthetized children.IEEE transactions on biomedical engineering, 53(11):2211–2219, 2006

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:01.096572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Pith citing papers

Observation 0241e36b-08eb-406b-b354-63d25a6569c3 · inbound

A Numerical Procedure for the Determination of the Pursuit Curve of Objects with Uniformly Accelerated Motion cites this paper.

A Numerical Procedure for the Determination of the Pursuit Curve of Objects with Uniformly Accelerated Motion VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T04:16:27.970183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:16:27.970183Z digest=sha256:f5b3feda616669d47ab3754a6cde74def3856bdc89e32443c12d0b863445f087

Observation cf230107-83f6-473e-92fb-adabd9213783 · inbound

Latent Diffusion Posterior Sampling with Surrogate Likelihood Guidance for PDE Inverse Problems cites this paper.

Latent Diffusion Posterior Sampling with Surrogate Likelihood Guidance for PDE Inverse Problems VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-04T14:39:58.505853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-26T02:42:32.734600Z digest=sha256:e3d113ccbc2ffeeeed36f2a6f498f5b544d6d41e5ebd211d4b4b817b8d14409a