Pith. sign in

Paper Citation Record · LEDGER

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

As of 10 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.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

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

  • verified exact0
  • verified fuzzy47
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:09.807675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:53.609348Z digest=sha256:2df5659683001a97851f5b02aba021ec2573792d879a4d13e642844dca3be292

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

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:53.680348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:53.680348Z digest=sha256:fb1cc8a3d2b51d1534325a9f480717152f4e1ccb232a1d69c95ad7b63937723d

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:09.670150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:53.833491Z digest=sha256:815eb77169c4c001e0265c07a4340b6448c516e650cae0cda02f59e8eac7d69e

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:09.421569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:53.898769Z digest=sha256:635e3aecbec386ec71f5531f575b527a86e3bbb709d1077f375c6a939370946b

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:09.228772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:53.974924Z digest=sha256:73b6f73af9efa379fd0f61f1fb3217479c0179b8e2e27dcf26203499a2459087

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

Resolution
unresolved
raw_fallback, observed 2026-08-06T04:14:09.018509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:54.070643Z digest=sha256:9116c311098189dfbf148561e0a68296425f2aa5f4364c5294953d80833e0f86

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

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:54.136752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:54.136752Z digest=sha256:9ed74edc3674f94a75de55ed3d02dadbda952b59c49dbf4f74131396006adfb5

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

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:54.203066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:54.203066Z digest=sha256:a708fc999e7eec3c81056fe7eb03c3aae4877f6772a883cd0e5fc826f3e8267a

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

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:54.278557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:54.278557Z digest=sha256:32b5055e02c6e83e8650fde58c60f62b554c09c2347040f13d14c637a088c62a

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:08.789856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:54.370471Z digest=sha256:43852f3ca217cd5ff83477ee10e42a9a52960d383a1838c59214340de06759a6

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:08.597121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:54.474737Z digest=sha256:d77bf9565a01b42b267630afdce74a61ddf9a56994d83ad53cc7cebf8fba9bbe

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

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:54.538871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:54.538871Z digest=sha256:3a1f790ad37d46c9ff5bc83d2fc8e150084f0be08f8f74d3911f53251b1a0ff3

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:08.439430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:54.607597Z digest=sha256:ade564ad27239cfe92afcdd314d94e1fa25282734721e634ee6949fd3c20641e

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:08.196844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:54.788624Z digest=sha256:2ee96788c1e7b499384c74f2cee76732b32c1d50e89b62b3787b7354af22ce3b

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:07.997869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:54.917027Z digest=sha256:31cdf679c0d5e01fda30dcc1b91f6055a9542b4dc8478148f36f69cebafeaa3a

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:07.766815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:54.974963Z digest=sha256:2d0703e51414e2eabc58327be5de8d6431677748f0abe799996f21501c726e59

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

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:55.078165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:55.078165Z digest=sha256:2c82420bedc20d8972d8a155c8beb2b0de16821e88068c6bf6f41ff4f16a25b7

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:07.585022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:55.218217Z digest=sha256:cbd647918654fa3317f4b2963196c916e461049f1b884733229ec91af113a651

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:07.324617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:55.295922Z digest=sha256:92a7dd9b60b710d5cc8124949286d82ac8a0be4d38db205a298865183560f5ec

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:07.095219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:55.356806Z digest=sha256:ffc4a11a5e2475c5fdb6fb0ffc275e3bf611ac7cd4976ce0af836f43e51f1e5d

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:06.901753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:55.440935Z digest=sha256:753fc8fa166ae13254cd4aa79f240e36d99c3680997bd772c52dc7a3a0da0b05

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:06.744466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:55.526714Z digest=sha256:9652c4075cab92dcbe0bee7a68fecbd2d9dbc04d89e6faa85e8b82fd78a5f375

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:06.589688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:55.605327Z digest=sha256:596d065538df57cdba54c17c54a3c233c955be1e6fcc9cf5126d5a6903b97e6c

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:06.395872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:55.694671Z digest=sha256:ca3868dd1851ff3fe01443b2678dfec31a41bedb968b9380fa9f1d9064435767

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:14:06.229491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:55.783309Z digest=sha256:f45e6a5063318df88457f3830f009dae1c1d705f5da01d7331881986a7c0c1d8

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

Resolution
unresolved
no resolver link, observed 2026-08-06T04:13:55.905263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:13:55.905263Z digest=sha256:5f432ae31c2dfc4e6bbf430098d81cde5ba92674502731727aa38f5c3cb71e72

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

Resolution
verified fuzzy
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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:55.979362Z digest=sha256:4672190ed2d17a32bd50a7c540f7b753e9f60dee0121e5d9f4145f48a7848bcd

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

Resolution
verified fuzzy
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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:56.117175Z digest=sha256:0f91244d59d4cf222e2238dafbb9b7c19e6f65fa2ff60eecccae2b2cd13906fe

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

Resolution
verified fuzzy
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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:56.239112Z digest=sha256:a308e8124a51d0d9fcbc08cd5b27e6305c3368488badb0016dd443ac2c74b56a

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

Resolution
verified fuzzy
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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:56.333741Z digest=sha256:a749acb24e7c017b10f8b0c748bdf5a163806fa02e01f8efb3227969ac9aeb11

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

Resolution
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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:56.410303Z digest=sha256:3c8ca459569be711303f430c725bc0d00c600f1e0e462c505bc725eba3c0277d

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

Resolution
verified fuzzy
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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:56.500134Z digest=sha256:df116ff807627ad9ff43c8660e382a3016ec450d3aa82de202ed8a4936a5be1b

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:56.560958Z digest=sha256:f4f4c94b5c3af0cb4b0f8aadf965c41e2c33c7b49f0ac6f0b426cf6fbbce9cb3

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:56.699640Z digest=sha256:82ed22e5baad677c6ff72aa57f2603b7f9129452c4ea0a1119cc9ef50acf779e

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:56.828678Z digest=sha256:461508386b987d6c1260996751d712496c8dd70a9705e50a55aaf878273638b2

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:56.909865Z digest=sha256:1245fe62f4cbe93d881c05206f682110a3facc363346a0799cf7e1c9c96b4ffa

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:57.001334Z digest=sha256:c4cc885a1046f35fc8fdc56ca125bcce1523e28e37fbc1614bea808d7b7cee51

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:57.083495Z digest=sha256:7c92b9cdca7d3bbc4cd91388ad4d3df8efbe0a91d3edca384582395c3af02c2d

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:57.175814Z digest=sha256:2dc4a28b1f2e9958c5e1073ab9c0ee5d612a061cdbdf83d2773285ec6ecd6afb

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:57.324066Z digest=sha256:54eff8abe6c1e7b66cac36520a1e9a31b11a827fdcd208d1244b10203860bed5

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=sha256:07efb8dbd8bfad371fb6877394849d9b86969c74739032c326ceea6f9b4ee059

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=sha256:7fb8e36a3afc0adef78812de910c5cf7c85034ed8bf8b3499a184f853b34a813

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:57.598769Z digest=sha256:16576cf717a21565ef80a75ed51010b1c2b088a3eb5713985534d655948e084d

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:b98c6707895842fcde94232488bda651331b3a4b25a21e4e214781243302db6b

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:57.774267Z digest=sha256:e6c849c665e8df0b7a1b378a77f3ec12cc55f53d549aad8730265891bb41195e

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:57.863950Z digest=sha256:98c49829922fe54ac2af9b1c0813c5f2c3a3f423abe5eb56bbc72c140928de25

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:57.992536Z digest=sha256:c69dd73277c9e131c100321e2fde5b4942b991b6af13ec18756531a62485c8d3

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=sha256:314aac9699a6330fd1aa1a37ed5ecea50296b2656988139ac1cc30081975f122

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:ea5aa9376e09e9d9d40616f41a2a634ab958b9102ad123400a859e6a07b903f5

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:58.320830Z digest=sha256:58e692cf02d053522b5fbdd2f0fa5e63b5156e685e2e557778c3dc0cf2df7aa3

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:ab8db26fa56a734e1aa64995bc5a966d8abe4faa150f6267b1a807fd1e1c9408

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:58.477953Z digest=sha256:c0f5563a8cc4897274fbdcdadc7e0ce24b5dacff13bfa5c86d7ef4df1cda16ed

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=sha256:4097309afed5852da1a589f71426424b8c2df0a1a67b68ec1993e9e39ec950ff

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:58.701407Z digest=sha256:aff6625f332016e060fafa9ac4dd537b775fec4194d7799af83e016d500b64aa

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:58.807444Z digest=sha256:b0d3b587f83c428430291e734cca6ad0e8bb368fa71c3478fc09e967d231685c

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:58.872156Z digest=sha256:8985409643ea35ecf3e17c420e94dd5c6c75f79a39485de3478640cffa794c26

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:af9fb70676ed1f3f5cce5081c3db3fa335ad02f1a72662d3b0cb62569fe0dcdf

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:59.021374Z digest=sha256:01d315dd5cf910a538ed81a2c76535b16c6383318e54fc8343e5a70bd011c693

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:59.098287Z digest=sha256:ebb174fb1572003c80e16b25faebf7f15996339807a6d4306ac0e9a4c13c49d5

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:59.224312Z digest=sha256:958ca17a9358dccd2da475b18c6f5c0db3254b9df2cc5bb1d82822b92f837bed

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:a477e5799d223dbbe0da343767dee6cb70a8fa8a1bd1cae26b97ccb438a92b10

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:dd297f784e3bcf5be5919ce46780ff5f7dcae02ce564ca2f8eb27450ef4212b6

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:59.652498Z digest=sha256:eb86fcc77f3182f4ae89b3ad112586690a12cd6bd65fc339de3f97016a7ebd87

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=sha256:0e2682b0c49c53252202f7f2d9ec6cae48a63208a18cb1a92ada21c82ddca1f5

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=sha256:48d5f06149f277967777e59291adaa25cfc08b2895fc5ab10cf246c7e6755728

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:13:59.994662Z digest=sha256:84398f85a2c619ab44430c09ae043f067f07e95fb2a1c0add30549de12ef2f9e

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:14:00.137822Z digest=sha256:32c9fcf27f73fa192d637c5b6ec431e77675f07c92bfb064c7831cc92d033e5f

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T04:14:00.311134Z digest=sha256:7131fb2e099f2dda14155acdf82f98cf531ef8d1f09a4a114530461652fc8a02

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=sha256:17912814b2fc4fd5830ffdd24240937a2817d4c39d368e9f42035109b913b277

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-26T02:42:32.734600Z digest=sha256:d75cfd99e6bbc0487c646c6a39728c009bd134e8ec263ab4280907981ad24e24