Paper Citation Record · LEDGER

Deep neural network approximations for Monte Carlo algorithms

As of 15 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 1 inbound Pith citation observation for arXiv:1908.10828.

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

pith.paper-citation-record.v1
1908.10828 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:39:29.678317Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

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

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-24T12:37:24.021894Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T12:39:29.086052Z

Reference resolution

55 of 55 outbound references displayed

verified exact8
verified fuzzy32
unresolved14
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 58fc7b9f-3781-477d-a845-a6164cf60705 · outbound

This paper cites Deep splitting method for parabolic PDEs.

Deep neural network approximations for Monte Carlo algorithms Deep splitting method for parabolic PDEs

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:29.498752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3badd1d-252d-4ff8-afba-4d1454903a24 · outbound

This paper cites Solving the Kolmogorov PDE by means of deep learning.

Deep neural network approximations for Monte Carlo algorithms Solving the Kolmogorov PDE by means of deep learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:29.503243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e3d1a14-18ce-458c-acfd-8ec3d85a80d3 · outbound

This paper cites Machine Learning Approximation Algorithms for High-Dimensional Fully Nonlinear Partial Diﬀerential Eq uations and Second-order Backward Stochastic Diﬀerential Equations.

Deep neural network approximations for Monte Carlo algorithms Machine Learning Approximation Algorithms for High-Dimensional Fully Nonlinear Partial Diﬀerential Eq uations and Second-order Backward Stochastic Diﬀerential Equations

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.374177Z

Source-reported events for the cited work

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

Observation ba55fbb8-6bfd-46ed-9331-3ecc715bb5cf · outbound

This paper cites Deep optimal stopping.

Deep neural network approximations for Monte Carlo algorithms Deep optimal stopping

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.364434Z

Source-reported events for the cited work

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

Observation ade606b0-3af4-4b27-a98f-6173c870dacc · outbound

This paper cites Solving high-dimensional optimal stopping problems using deep learning.

Deep neural network approximations for Monte Carlo algorithms Solving high-dimensional optimal stopping problems using deep learning

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:39:29.998521Z

Source-reported events for the cited work

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

Observation 6b868d3a-2380-4195-8349-5ae9604fe3d3 · outbound

This paper cites Dynamic programming.

Deep neural network approximations for Monte Carlo algorithms Dynamic programming

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.354755Z

Source-reported events for the cited work

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

Observation 5714f129-161b-4190-b57f-fd69dd2cc67f · outbound

This paper cites Applications of variational inequalities in stochastic control , vol.

Deep neural network approximations for Monte Carlo algorithms Applications of variational inequalities in stochastic control , vol

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.345141Z

Source-reported events for the cited work

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

Observation 78aaa35d-6d46-460d-94ec-e1af0f82ccec · outbound

This paper cites A uniﬁed deep artiﬁcial neural network ap- proach to partial diﬀerential equations in complex geometries.

Deep neural network approximations for Monte Carlo algorithms A uniﬁed deep artiﬁcial neural network ap- proach to partial diﬀerential equations in complex geometries

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.335605Z

Source-reported events for the cited work

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

Observation cda85c68-7319-48ea-97eb-f94f9a18a3fc · outbound

This paper cites Analysis of the Generalization Error: Empirical Risk Minimization over Deep Artificial Neural Networks Overcomes the Curse of Dimensionality in the Numerical Approximation of Black-Scholes Partial Differential Equations.

Deep neural network approximations for Monte Carlo algorithms Analysis of the Generalization Error: Empirical Risk Minimization over Deep Artificial Neural Networks Overcomes the Curse of Dimensionality in the Numerical Approximation of Black-Scholes Partial Differential Equations

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:39:29.985515Z

Source-reported events for the cited work

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

Observation e6e8a025-78f7-4c90-87e0-d77f40c0b475 · outbound

This paper cites Machine learning for semi linear PDEs.

Deep neural network approximations for Monte Carlo algorithms Machine learning for semi linear PDEs

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.326385Z

Source-reported events for the cited work

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

Observation 0981ef87-bb00-4149-8c33-8e40e1cb7a8a · outbound

This paper cites an unresolved cited work.

Deep neural network approximations for Monte Carlo algorithms Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-14T10:39:30.317181Z

Source-reported events for the cited work

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

Observation 2a28f3ce-de77-4762-a312-fe55256efbda · outbound

This paper cites E., Yu, D., Deng, L., and Acero, A.

Deep neural network approximations for Monte Carlo algorithms E., Yu, D., Deng, L., and Acero, A

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.308162Z

Source-reported events for the cited work

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

Observation 96130df5-274a-4510-ab4a-5d964f255d57 · outbound

This paper cites A Discussion on Solving Partial Differential Equations using Neural Networks.

Deep neural network approximations for Monte Carlo algorithms A Discussion on Solving Partial Differential Equations using Neural Networks

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:39:29.972351Z

Source-reported events for the cited work

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

Observation e00f82a3-18ab-4326-aa77-43bb36e0712b · outbound

This paper cites Deep learning-based numerical meth- ods for high-dimensional parabolic partial diﬀerential equations an d backward stochastic diﬀerential equations.

Deep neural network approximations for Monte Carlo algorithms Deep learning-based numerical meth- ods for high-dimensional parabolic partial diﬀerential equations an d backward stochastic diﬀerential equations

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.298932Z

Source-reported events for the cited work

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

Observation 52b0e927-778a-47b5-8849-58bf94c90855 · outbound

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

Deep neural network approximations for Monte Carlo algorithms The deep Ritz method: A deep learning-based numerical algorithm for solving variational problems

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.289168Z

Source-reported events for the cited work

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

Observation d9793405-7245-4622-9732-ea9d761a68d6 · outbound

This paper cites DNN Ex- pression Rate Analysis of High-dimensional PDEs: Application to Optio n Pric- ing.

Deep neural network approximations for Monte Carlo algorithms DNN Ex- pression Rate Analysis of High-dimensional PDEs: Application to Optio n Pric- ing

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.279777Z

Source-reported events for the cited work

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

Observation d8c709a3-7a54-4d0f-8ddb-f8c4111d48b3 · outbound

This paper cites Deep reinforcement learn- ing for partial diﬀerential equation control.

Deep neural network approximations for Monte Carlo algorithms Deep reinforcement learn- ing for partial diﬀerential equation control

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.270105Z

Source-reported events for the cited work

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

Observation 41669566-e0e9-46be-b7ac-9ad2dbb3a59c · outbound

This paper cites Asymptotic expansion as prior knowledge in deep learning method for high dimensional BSDEs.

Deep neural network approximations for Monte Carlo algorithms Asymptotic expansion as prior knowledge in deep learning method for high dimensional BSDEs

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.260685Z

Source-reported events for the cited work

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

Observation 027e878c-9fc9-4f0d-9bbb-9b13758a39de · outbound

This paper cites Variance Reduction Applied to Machine Learning for Pricing Bermudan/American Options in High Dimension.

Deep neural network approximations for Monte Carlo algorithms Variance Reduction Applied to Machine Learning for Pricing Bermudan/American Options in High Dimension

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:39:29.959323Z

Source-reported events for the cited work

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

Observation e4584470-d1f1-429b-a0b0-e3478c726a43 · outbound

This paper cites Speech recognition with deep recurrent neural networks.

Deep neural network approximations for Monte Carlo algorithms Speech recognition with deep recurrent neural networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.251390Z

Source-reported events for the cited work

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

Observation 6512c763-88f1-42a6-b8fe-090efed0c290 · outbound

This paper cites A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations.

Deep neural network approximations for Monte Carlo algorithms A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:29.567946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21c3664a-7cdf-4956-bdf0-bc9fe3e66a91 · outbound

This paper cites Space-time error estimates for deep neural network approximations for differential equations.

Deep neural network approximations for Monte Carlo algorithms Space-time error estimates for deep neural network approximations for differential equations

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:29.571077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa6488fe-cee7-4991-a160-db64de21089a · outbound

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

Deep neural network approximations for Monte Carlo algorithms Solving high-dimensional partial diﬀer- ential equations using deep learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.241519Z

Source-reported events for the cited work

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

Observation 40de4db3-b036-4d8b-9d39-cc26fd6792e4 · outbound

This paper cites Convergence of the Deep BSDE Method for Coupled FBSDEs.

Deep neural network approximations for Monte Carlo algorithms Convergence of the Deep BSDE Method for Coupled FBSDEs

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:39:29.927986Z

Source-reported events for the cited work

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

Observation fb21eacf-787f-4c9a-b49e-e6b90f03eafd · outbound

This paper cites Deep Primal-Dual Algorithm for BSDEs: Applica- tions of Machine Learning to CV A and IM.

Deep neural network approximations for Monte Carlo algorithms Deep Primal-Dual Algorithm for BSDEs: Applica- tions of Machine Learning to CV A and IM

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.232088Z

Source-reported events for the cited work

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

Observation 65080fae-bd4c-4e03-a3d6-20ce35e0f1d2 · outbound

This paper cites E., Mohamed, A.-r., Jaitly , N., Senior, A., V anhoucke, V., Nguyen, P., Sainath, T.

Deep neural network approximations for Monte Carlo algorithms E., Mohamed, A.-r., Jaitly , N., Senior, A., V anhoucke, V., Nguyen, P., Sainath, T

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.223066Z

Source-reported events for the cited work

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

Observation d462650c-84ce-4242-a9d0-ac5f56b4ca1e · outbound

This paper cites Convolutional neural network ar- chitectures for matching natural language sentences.

Deep neural network approximations for Monte Carlo algorithms Convolutional neural network ar- chitectures for matching natural language sentences

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.213212Z

Source-reported events for the cited work

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

Observation 931e6ff1-8a84-493f-b7a8-b0b1724bfe82 · outbound

This paper cites an unresolved cited work.

Deep neural network approximations for Monte Carlo algorithms Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-14T10:39:30.203440Z

Source-reported events for the cited work

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

Observation 1e02a9ea-98ae-44e5-bf35-fdbd15f3619e · outbound

This paper cites Some machine learning schemes for high-dimensional nonlinear PDEs.

Deep neural network approximations for Monte Carlo algorithms Some machine learning schemes for high-dimensional nonlinear PDEs

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:29.592708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1075d92-4ded-4507-aea7-264bc3ab3d8e · outbound

This paper cites A proof that rectified deep neural networks overcome the curse of dimensionality in the numerical approximation of semilinear heat equations.

Deep neural network approximations for Monte Carlo algorithms A proof that rectified deep neural networks overcome the curse of dimensionality in the numerical approximation of semilinear heat equations

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:39:29.858463Z

Source-reported events for the cited work

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

Observation 19a27fba-8322-46b3-baa8-a6b289fe037d · outbound

This paper cites Deep Curve-dependent PDEs for affine rough volatility.

Deep neural network approximations for Monte Carlo algorithms Deep Curve-dependent PDEs for affine rough volatility

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:39:29.844595Z

Source-reported events for the cited work

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

Observation ecfc1226-a8b1-4783-8d02-f21732d264ff · outbound

This paper cites A proof that deep artificial neural networks overcome the curse of dimensionality in the numerical approximation of Kolmogorov partial differential equations with constant diffusion and nonlinear drift coefficients.

Deep neural network approximations for Monte Carlo algorithms A proof that deep artificial neural networks overcome the curse of dimensionality in the numerical approximation of Kolmogorov partial differential equations with constant diffusion and nonlinear drift coefficients

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:29.602442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a516ed22-02ea-454a-994a-eec889411594 · outbound

This paper cites Numerical solution of elliptic partial diﬀerential equation using radial basis function neura l networks.

Deep neural network approximations for Monte Carlo algorithms Numerical solution of elliptic partial diﬀerential equation using radial basis function neura l networks

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.193504Z

Source-reported events for the cited work

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

Observation 97109eb2-097d-4b11-b76c-ddb0bb869ca2 · outbound

This paper cites A convolu- tional neural network for modelling sentences.

Deep neural network approximations for Monte Carlo algorithms A convolu- tional neural network for modelling sentences

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.183816Z

Source-reported events for the cited work

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

Observation 64a51c9d-1bf0-40e1-a5c0-55f3e4cd9b03 · outbound

This paper cites an unresolved cited work.

Deep neural network approximations for Monte Carlo algorithms Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-08-14T10:39:30.174283Z

Source-reported events for the cited work

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

Observation 36331dd0-55cc-49ee-aba1-dbc6c841feb8 · outbound

This paper cites A Theoretical Analysis of Deep Neural Networks and Parametric PDEs.

Deep neural network approximations for Monte Carlo algorithms A Theoretical Analysis of Deep Neural Networks and Parametric PDEs

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:29.614742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 993fc583-6767-4ff6-97dc-228fa54f96f6 · outbound

This paper cites E., Likas, A., and Fotiadis, D.

Deep neural network approximations for Monte Carlo algorithms E., Likas, A., and Fotiadis, D

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.164917Z

Source-reported events for the cited work

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

Observation 57cf2c04-88a7-4127-a4a3-9d228bdd47fd · outbound

This paper cites PDE-Net: Learning PDEs from Data.

Deep neural network approximations for Monte Carlo algorithms PDE-Net: Learning PDEs from Data

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.155403Z

Source-reported events for the cited work

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

Observation 094cf00d-d2c8-4be8-ad80-2e67462bcb68 · outbound

This paper cites Deep learning observables in computational fluid dynamics.

Deep neural network approximations for Monte Carlo algorithms Deep learning observables in computational fluid dynamics

Reference 39

Resolution: metadata mismatch; local_arxiv, observed 2026-08-14T10:39:29.813831Z

Source-reported events for the cited work

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

Observation 8a362de8-ca8d-4423-9d2d-34f8c2ad18be · outbound

This paper cites an unresolved cited work.

Deep neural network approximations for Monte Carlo algorithms Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-08-14T10:39:30.145706Z

Source-reported events for the cited work

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

Observation b0a57744-2f8c-426f-b370-f9f8712afe7b · outbound

This paper cites J., and Fern ´andez, A.

Deep neural network approximations for Monte Carlo algorithms J., and Fern ´andez, A

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.135684Z

Source-reported events for the cited work

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

Observation f6648e70-a0d3-4e58-9958-92b4ad38e54e · outbound

This paper cites Tractability of multivariate problems.

Deep neural network approximations for Monte Carlo algorithms Tractability of multivariate problems

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.126377Z

Source-reported events for the cited work

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

Observation 712dbfa7-83e2-45bd-824b-d5c9982f625b · outbound

This paper cites Tractability of multivariate problems.

Deep neural network approximations for Monte Carlo algorithms Tractability of multivariate problems

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.116573Z

Source-reported events for the cited work

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

Observation 61aa838f-e4be-44a0-9534-7cf2594f2245 · outbound

This paper cites Neural networks-based backward scheme for fully nonlinear PDEs.

Deep neural network approximations for Monte Carlo algorithms Neural networks-based backward scheme for fully nonlinear PDEs

Reference 44

Resolution: verified exact; raw_fallback, observed 2026-08-14T10:39:29.798915Z

Source-reported events for the cited work

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

Observation 2ef84694-3aad-4a43-87d0-fcfac025a915 · outbound

This paper cites Deep hidden physics models: Deep learning of nonlinear partial diﬀerential equations.

Deep neural network approximations for Monte Carlo algorithms Deep hidden physics models: Deep learning of nonlinear partial diﬀerential equations

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.107231Z

Source-reported events for the cited work

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

Observation bd7bc629-6375-4edd-a90d-420f76985367 · outbound

This paper cites Rectified deep neural networks overcome the curse of dimensionality for nonsmooth value functions in zero-sum games of nonlinear stiff systems.

Deep neural network approximations for Monte Carlo algorithms Rectified deep neural networks overcome the curse of dimensionality for nonsmooth value functions in zero-sum games of nonlinear stiff systems

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:29.649643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48cc8bbd-df98-42f5-badc-0609773a86bf · outbound

This paper cites Deep learning detecting fraud in credit card transactions.

Deep neural network approximations for Monte Carlo algorithms Deep learning detecting fraud in credit card transactions

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.097660Z

Source-reported events for the cited work

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

Observation 8eb8fe8f-74ae-4774-b64d-e9c1cd762814 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Deep neural network approximations for Monte Carlo algorithms Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-14T10:39:29.656731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 443f1acf-90b3-4132-b548-6e7e4bba9c42 · outbound

This paper cites DGM: A deep learning algorithm for solving partial diﬀerential equations.

Deep neural network approximations for Monte Carlo algorithms DGM: A deep learning algorithm for solving partial diﬀerential equations

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.087909Z

Source-reported events for the cited work

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

Observation 535f13b6-d678-4f71-a5fb-00058aceca44 · outbound

This paper cites Deepface: Closing the gap to human-level performance in face veriﬁcation.

Deep neural network approximations for Monte Carlo algorithms Deepface: Closing the gap to human-level performance in face veriﬁcation

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.078464Z

Source-reported events for the cited work

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

Observation 24c82622-5c6b-49b2-964d-a5213b27d5da · outbound

This paper cites Solving inverse problems in nonlinear PDEs by recurrent neural networks.

Deep neural network approximations for Monte Carlo algorithms Solving inverse problems in nonlinear PDEs by recurrent neural networks

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.067879Z

Source-reported events for the cited work

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

Observation b9b871e6-c858-46e4-a702-4d40e9c41e4a · outbound

This paper cites Deep & cross network for ad click predictions.

Deep neural network approximations for Monte Carlo algorithms Deep & cross network for ad click predictions

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.057766Z

Source-reported events for the cited work

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

Observation beee2f90-4472-4cb8-bff4-1005739721c5 · outbound

This paper cites Face recognition based on deep learning.

Deep neural network approximations for Monte Carlo algorithms Face recognition based on deep learning

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.047634Z

Source-reported events for the cited work

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

Observation 75f330af-ea3c-4a63-abe7-93bbdd6a31fb · outbound

This paper cites J., and Sim, K.

Deep neural network approximations for Monte Carlo algorithms J., and Sim, K

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:39:30.037443Z

Source-reported events for the cited work

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

Observation 3133b7cb-446f-4a16-8a2c-57a3f31d746e · outbound

This paper cites an unresolved cited work.

Deep neural network approximations for Monte Carlo algorithms Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-14T10:39:30.026994Z

Source-reported events for the cited work

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

Pith citing papers

Observation 39bcd1ef-2639-40cb-80df-0f7cc4a7d3c8 · inbound

Deep neural network approximation theory for high-dimensional functions cites this paper.

Deep neural network approximation theory for high-dimensional functions Deep neural network approximations for Monte Carlo algorithms

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-24T12:39:29.089898Z

Source-reported events for the cited work

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