Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T04:14:00.311134Z
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T04:14:00.311134Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T04:16:27.970183Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T14:39:58.504186Z
68 of 68 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 035d2a00-97e3-40a5-8f88-4c69d2825245 · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Springer, 2003
Reference 1
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.
Observation a887bd5d-d6df-4ca2-9953-7b157ebd7cd8 · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Efficient Concentration with Gaussian Approximation
Reference 2
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation db4e463d-7ec3-4516-bd7f-8c43c15e41f2 · outbound
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
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.
Observation 66cc3a71-eced-407a-b219-07864abf96ff · outbound
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
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.
Observation a30b39e5-001e-4628-95b0-e82e4be568bb · outbound
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
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.
Observation f70940d5-8d9d-4019-b65d-8c563594cf17 · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Unresolved cited work
Reference 6
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.
Observation faf5410d-9e89-4019-94a8-b9eae164168b · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f7e03bb8-7712-4924-8b7d-f30e6fcb3637 · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Unresolved cited work
Reference 8
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 33b51a8e-c4cb-47d8-9733-88a163d3149b · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a2d3a202-9cdb-4ad8-ab83-0b4a25409271 · outbound
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
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.
Observation 04d9a0ad-0507-44b5-bfcb-c45d03aa3482 · outbound
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
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.
Observation d7b8d712-8d5d-4b77-a343-1f97ccf84e30 · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c6867601-1302-43d1-8cf6-33bfc27f0df1 · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Strong approximations of bivariate uniform empirical processes
Reference 13
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.
Observation 141ad869-3a93-43a2-aab4-21adab9567e4 · outbound
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
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.
Observation cb37c1e9-4096-4cc0-b497-2b25ad86dd15 · outbound
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
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.
Observation 9f546998-01f8-4bea-b801-f07bc5c19180 · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations From stein identities to moderate deviations
Reference 16
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.
Observation 6cee9a47-9d12-447e-9164-7ccfeeb065bf · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6c60221e-41bb-42eb-be0e-3abe3413c000 · outbound
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
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.
Observation e5afcefc-ff23-4cd0-99a3-20c5b7019665 · outbound
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
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.
Observation 8872d15d-11fb-497d-86fb-5cf605ec117d · outbound
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
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.
Observation 8450e642-9d89-49af-8d77-344fff0863bd · outbound
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
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.
Observation bd6e6dda-40d3-48be-955d-639ec8e8d64d · outbound
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
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.
Observation 72bc6932-1bc1-410a-b93e-4384b1e8e10f · outbound
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
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.
Observation 5250e35d-369b-40a6-95e3-a47bc67f0863 · outbound
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
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.
Observation 281d7f57-acb1-49d4-aaf0-5f683570f918 · outbound
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
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.
Observation 17fa2e4e-61ff-4959-bac9-25368df64268 · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Cambridge University Press, 2014
Reference 26
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 63ee4565-67a7-4075-a758-1fde8378b3ed · outbound
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
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.
Observation d334ae87-3335-420e-b00a-5a0bd147f76f · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Springer Science & Business Media, 2012
Reference 28
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.
Observation f38df772-b2fd-4b12-8bf4-d597aca72ba8 · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Courier Corporation, 2012
Reference 29
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.
Observation a959bf94-d3a9-4304-8d3c-28e3c237a8d8 · outbound
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
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.
Observation 107d4fd7-50a0-456a-bc50-443756970a69 · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Springer Science & Business Media, 2012
Reference 31
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.
Observation 4bb65565-7292-4e14-b78f-1c1eced83855 · outbound
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
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.
Observation ab379614-7db5-465a-b7b4-98cd65f755d1 · outbound
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
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.
Observation 5d9320c4-ac1a-4dae-b34c-892fb86b9da9 · outbound
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
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.
Observation 666ac376-e542-4b52-a29d-9b5d08d132e4 · outbound
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
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.
Observation 9033b867-ea47-4211-9ad9-cda6be258130 · outbound
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
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.
Observation 33e33659-b0d7-4d67-815b-ebf9b761f018 · outbound
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
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.
Observation 8e1c2302-9d37-469a-be96-50dc3d037396 · outbound
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
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.
Observation 0a65937c-db69-42b3-b862-a672beed37df · outbound
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
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.
Observation 9a1184a9-3483-4fff-89df-85e2baa4c18a · outbound
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
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.
Observation a1eafe7b-ad71-4322-a4a3-9a1b8d7373df · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e99e1c0a-f8ac-43a0-8e4c-0a7b55d2562c · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Quantile coupling inequalities and their applications
Reference 42
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 410bd02b-15bd-42ce-8613-0c38b7a967cb · outbound
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
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.
Observation 4e8861b8-62b2-4c3c-8cf7-930a59b59c9e · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations John wiley & sons, 2020
Reference 44
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6f7e00c7-53ac-4b6c-82d9-c40c29a10b97 · outbound
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
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.
Observation e7837efc-f6fc-4dbc-9683-46f48b4d76ef · outbound
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
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.
Observation e670e80c-ab41-4661-8c75-3dd7d5d6c848 · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations A note on Burkholder-Rosenthal inequality.Bull
Reference 47
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.
Observation 8409fde2-e3a6-466a-b0dc-8f9ac1b26a78 · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f7bad74b-82f4-4150-8407-441d828114cd · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 83678556-6b02-4979-9c23-8a0822ba7ef9 · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Unresolved cited work
Reference 50
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.
Observation 36cf916b-4786-4b34-83a2-7540daed40af · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Springer Science & Business Media, 2012
Reference 51
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1a6a9894-aacd-4ab3-b411-a51762c5d947 · outbound
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
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.
Observation d902829b-1f90-4251-8731-daecbe2ac58a · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations John Wiley & Sons, 2003
Reference 53
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fbba294c-9a17-4a10-95dc-519494f253d0 · outbound
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
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.
Observation ee767303-ae64-46d0-9b3f-6111a4ff2f97 · outbound
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
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.
Observation b49ba4db-37ee-4b0e-9738-5f8695d70dc3 · outbound
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
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.
Observation f53c2363-5a2b-4853-b0e9-762683941240 · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Reducing sequential change detection to sequential estimation
Reference 57
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0d5e04ac-6ce0-4ba8-873f-78531c463f10 · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Springer, 2004
Reference 58
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.
Observation 3789902b-67ec-445e-824b-04d7b4d1ccae · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Staudacher, S
Reference 59
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.
Observation d3723309-ad58-4df3-b4ea-0ed5a0b92b5e · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations John Wiley & Sons, 2001
Reference 60
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.
Observation 96a77237-fb32-45ed-8ebd-a93bdd308137 · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations Survival Multiarmed Bandits with Bootstrapping Methods
Reference 61
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6492fea4-946c-4db1-951a-12adfa72ba3b · outbound
VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model For Parametric Partial Differential Equations American Mathematical Soc., 2003
Reference 62
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d3d0d7f1-23ca-48b2-9cb3-0cbb18000cf8 · outbound
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
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.
Observation 0351c1d8-c5ea-40a5-a1b0-40aa8ea9ca0d · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 10a38bf1-0170-4fb0-941f-b132844931e6 · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b0987185-aed1-4c4c-9682-fae9f95f51fc · outbound
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
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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4b82fc2f-b6aa-438e-a050-ec752c0d3720 · outbound
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
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Observation 5386f057-cd97-4d95-9e1e-84a90876b992 · outbound
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
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Observation 0241e36b-08eb-406b-b354-63d25a6569c3 · inbound
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
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Observation cf230107-83f6-473e-92fb-adabd9213783 · inbound
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
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