Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:51:24.498177Z
Paper Citation Record · LEDGER
Computational Math with Neural Networks is Hard
As of 10 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 1 inbound Pith citation observation for arXiv:2505.17751.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-09T19:35:31.236089Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T15:36:08.139823Z
Reference resolution
54 of 54 outbound references displayed
- verified exact11
- verified fuzzy21
- unresolved19
- parse uncertain0
- malformed identifier2
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 69b391a1-4646-4e13-b9c2-e66c0c843cc8 · outbound
This paper cites Neural Operators for Accelerating Scientific Simulations and Design.
Computational Math with Neural Networks is Hard Neural Operators for Accelerating Scientific Simulations and Design
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:20.129523Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c50a3091-b8ba-4be2-966b-fefc2f229d89 · outbound
This paper cites Volumes of sections of cubes and related problems.
Computational Math with Neural Networks is Hard Volumes of sections of cubes and related problems
Reference 2
- Resolution
- verified exact
- doi, observed 2026-08-07T14:51:27.416253Z
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.
Observation 9d1343d5-0777-4225-941d-874970fc2cda · outbound
This paper cites Neural networks as smooth priors for inverse problems for PDEs.
Computational Math with Neural Networks is Hard Neural networks as smooth priors for inverse problems for PDEs
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:33.427328Z
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.
Observation ae75b1e7-c6e4-4845-80db-46e18b076d8a · outbound
This paper cites Some remarkable properties of sinc and related integrals.
Computational Math with Neural Networks is Hard Some remarkable properties of sinc and related integrals
Reference 4
- Resolution
- verified exact
- doi, observed 2026-08-07T14:51:27.177124Z
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.
Observation 0c88e1ec-562f-4ae2-90b5-a012e66d00e4 · outbound
This paper cites The complexity of satisfiability of small depth circuits.
Computational Math with Neural Networks is Hard The complexity of satisfiability of small depth circuits
Reference 5
- Resolution
- verified exact
- doi, observed 2026-08-07T14:51:26.879732Z
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.
Observation 9f519fe7-a29f-448f-86e7-74102bfb6dce · outbound
This paper cites Solving the quantum many-body problem with artificial neural networks.
Computational Math with Neural Networks is Hard Solving the quantum many-body problem with artificial neural networks
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:20.562056Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f06426b8-ebb8-4d73-8338-6c388d0bc7d7 · outbound
This paper cites an unresolved cited work.
Computational Math with Neural Networks is Hard Unresolved cited work
Reference 7
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:51:33.136400Z
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.
Observation 7c88b814-5e69-40a2-bba8-032c684073db · outbound
This paper cites Approximation algorithms for training one-node ReLU neural networks.
Computational Math with Neural Networks is Hard Approximation algorithms for training one-node ReLU neural networks
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:20.729038Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 54455d0a-3a66-44d3-b060-d3c984658103 · outbound
This paper cites High-dimensional integration: The quasi-Monte Carlo way.
Computational Math with Neural Networks is Hard High-dimensional integration: The quasi-Monte Carlo way
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:32.858327Z
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.
Observation 82dc33c1-b458-44e3-bfa4-bbe71a2975db · outbound
This paper cites Expression of Fractals Through Neural Network Functions.
Computational Math with Neural Networks is Hard Expression of Fractals Through Neural Network Functions
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:32.576739Z
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.
Observation 0cfba83c-1fe8-406e-af44-9bbaaa6bd9fe · outbound
This paper cites Algorithms for solving high dimensional PDEs: from nonlinear Monte Carlo to machine learning.
Computational Math with Neural Networks is Hard Algorithms for solving high dimensional PDEs: from nonlinear Monte Carlo to machine learning
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:32.343175Z
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.
Observation 5dfd182e-2090-48f8-aa13-56240e4ccfa6 · outbound
This paper cites The Deep Ritz Method: A Deep Learning-Based Numerical Algorithm for Solving Variational Problems.
Computational Math with Neural Networks is Hard The Deep Ritz Method: A Deep Learning-Based Numerical Algorithm for Solving Variational Problems
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:21.054908Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8e2a0f69-d819-4870-a359-e46108422383 · outbound
This paper cites The deep Ritz method: a deep learning-based numerical algorithm for solving variational problems.
Computational Math with Neural Networks is Hard The deep Ritz method: a deep learning-based numerical algorithm for solving variational problems
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:32.116424Z
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.
Observation 9c081924-db4b-4489-9d75-410ad89deb60 · outbound
This paper cites Feischl, A.
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:31.849699Z
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.
Observation 863b5661-cfac-47e5-b7b5-e318fdcad6fa · outbound
This paper cites Deep Neural Networks and Adaptive Quadrature for Solving Variational Problems.
Computational Math with Neural Networks is Hard Deep Neural Networks and Adaptive Quadrature for Solving Variational Problems
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:31.559458Z
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.
Observation 16c6368a-bc1d-474b-872e-7e7b968c979c · outbound
This paper cites Hyperplane sections of the n-dimensional cube.
Computational Math with Neural Networks is Hard Hyperplane sections of the n-dimensional cube
Reference 16
- Resolution
- verified exact
- doi, observed 2026-08-07T14:51:26.719376Z
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.
Observation 33885e21-5e72-4a4e-8a46-ed6931ec7dde · outbound
This paper cites Training Neural Networks is NP-Hard in Fixed Dimension.
Computational Math with Neural Networks is Hard Training Neural Networks is NP-Hard in Fixed Dimension
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:21.496167Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 41775334-c6a2-4926-8f96-5bf98e390e67 · outbound
This paper cites Gold-standard solutions to the Schr\"odinger equation using deep learning: How much physics do we need?.
Computational Math with Neural Networks is Hard Gold-standard solutions to the Schr\"odinger equation using deep learning: How much physics do we need?
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:21.571889Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 452b2b57-0fc0-4f2b-9fe1-394388d566b2 · outbound
This paper cites Gilbarg and N.
Computational Math with Neural Networks is Hard Gilbarg and N
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:31.243302Z
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.
Observation ba7b9896-4936-4718-abbb-78565bddd49e · outbound
This paper cites Analysis of preintegration followed by quasi–Monte Carlo integration for distribution functions and densities.
Computational Math with Neural Networks is Hard Analysis of preintegration followed by quasi–Monte Carlo integration for distribution functions and densities
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:30.962126Z
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.
Observation 3fec6d3b-ebed-4cdc-99df-d0b8aacb908e · outbound
This paper cites Tight hardness results for training depth-2 ReLU networks.
Computational Math with Neural Networks is Hard Tight hardness results for training depth-2 ReLU networks
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:30.718641Z
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.
Observation f9ff6de6-19d9-4c07-a6e9-c2a3c11ba366 · outbound
This paper cites Hierarchical singular value decomposition of tensors.
Computational Math with Neural Networks is Hard Hierarchical singular value decomposition of tensors
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:22.079096Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ac248f02-0650-42d2-8242-5a8672b44647 · outbound
This paper cites A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differen- tial equations.
Computational Math with Neural Networks is Hard A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differen- tial equations
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:30.470017Z
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.
Observation a9ca1ec1-0446-4bf7-939f-1c1c6c9d39aa · outbound
This paper cites Theory-to-Practice Gap for Neural Networks and Neural Operators.
Computational Math with Neural Networks is Hard Theory-to-Practice Gap for Neural Networks and Neural Operators
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:22.262827Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fa7f7882-6c23-4d35-8216-59f0427c8de2 · outbound
This paper cites Proof of the theory-to-practice gap in deep learning via sampling complexity bounds for neural network approximation spaces.
Computational Math with Neural Networks is Hard Proof of the theory-to-practice gap in deep learning via sampling complexity bounds for neural network approximation spaces
Reference 25
- Resolution
- verified exact
- doi, observed 2026-08-07T14:51:26.110580Z
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.
Observation f4dce1b6-c751-419c-8b28-f4ca0bbc7e7d · outbound
This paper cites A new scheme for the tensor representation.
Computational Math with Neural Networks is Hard A new scheme for the tensor representation
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:22.429773Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9213709c-dbe7-4ef1-b1fd-031a1a6aec43 · outbound
This paper cites Solving high-dimensional eigenvalue problems using deep neural networks: A diffusion Monte Carlo like approach.
Computational Math with Neural Networks is Hard Solving high-dimensional eigenvalue problems using deep neural networks: A diffusion Monte Carlo like approach
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:30.241936Z
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.
Observation 6dcc9eb0-2d25-4ea8-a5e9-bca49b71e77c · outbound
This paper cites Neural and spectral operator surrogates: unified construction and expression rate bounds.
Computational Math with Neural Networks is Hard Neural and spectral operator surrogates: unified construction and expression rate bounds
Reference 28
- Resolution
- verified exact
- doi, observed 2026-08-07T14:51:25.721230Z
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.
Observation b9358824-6eff-41eb-8e35-bfca58aa45c7 · outbound
This paper cites On the complexity of k-SAT.
Computational Math with Neural Networks is Hard On the complexity of k-SAT
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:30.084356Z
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.
Observation 760c55bd-665b-4d57-b6d3-6ddd4699d3c5 · outbound
This paper cites Which Problems Have Strongly Exponential Complex- ity?.
Computational Math with Neural Networks is Hard Which Problems Have Strongly Exponential Complex- ity?
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:29.942126Z
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.
Observation 5745fecf-3a01-4627-ae1a-bcac443d7417 · outbound
This paper cites QTT approximation of elliptic solution operators in higher dimensions.
Computational Math with Neural Networks is Hard QTT approximation of elliptic solution operators in higher dimensions
Reference 31
- Resolution
- verified exact
- doi, observed 2026-08-07T14:51:25.355110Z
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.
Observation 11d7ed3a-7676-4627-adb5-1042b62ca973 · outbound
This paper cites Operator Learning: Algorithms and Analysis.
Computational Math with Neural Networks is Hard Operator Learning: Algorithms and Analysis
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:22.985705Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2b0f50f5-89d0-4089-88ec-df60a3ddfc94 · outbound
This paper cites The Decision Problem for a Class of First-Order Formulas in Which all Disjunctions are Binary.
Computational Math with Neural Networks is Hard The Decision Problem for a Class of First-Order Formulas in Which all Disjunctions are Binary
Reference 33
- Resolution
- verified exact
- doi, observed 2026-08-07T14:51:24.970549Z
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.
Observation a48c3d4f-80a9-4529-9fed-8e7b0dfdd69d · outbound
This paper cites Error estimates for DeepONets: a deep learning framework in infinite dimensions.
Computational Math with Neural Networks is Hard Error estimates for DeepONets: a deep learning framework in infinite dimensions
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:23.119649Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5082aef0-c3b7-41e2-9700-b20562466c04 · outbound
This paper cites Neural Networks are Integrable.
Computational Math with Neural Networks is Hard Neural Networks are Integrable
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T14:51:27.681119Z
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.
Observation 16c992a7-f03c-4364-97d0-caa2f2c08a32 · outbound
This paper cites Exponential ReLU neural network approximation rates for point and edge singularities.
Computational Math with Neural Networks is Hard Exponential ReLU neural network approximation rates for point and edge singularities
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:29.828033Z
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.
Observation b45db3c4-7ad2-4baa-a168-8f799e7bf872 · outbound
This paper cites Marcati and C.
Computational Math with Neural Networks is Hard Marcati and C
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:23.476015Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 34e3e47a-250a-4d61-9ba0-8d33959db929 · outbound
This paper cites Deep learning in high dimension: ReLU neural network expression for Bayesian PDE inversion.
Computational Math with Neural Networks is Hard Deep learning in high dimension: ReLU neural network expression for Bayesian PDE inversion
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:29.699650Z
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.
Observation 9b49969a-a903-452a-a8e3-455fa77cb572 · outbound
This paper cites Approximation of 2 d × 2d matrices using tensor decomposition.
Computational Math with Neural Networks is Hard Approximation of 2 d × 2d matrices using tensor decomposition
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:23.640204Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation beef8bfb-c5c3-4c79-bfec-72a8dbc9e8a7 · outbound
This paper cites Topological properties of the set of functions generated by neural networks of fixed size.
Computational Math with Neural Networks is Hard Topological properties of the set of functions generated by neural networks of fixed size
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:23.700826Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c1a26a04-2c60-4872-a536-4803270ce023 · outbound
This paper cites On the difference between Turing machine time and random-access machine time.
Computational Math with Neural Networks is Hard On the difference between Turing machine time and random-access machine time
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:29.587670Z
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.
Observation fdf6c7c0-e497-4dc0-a5c1-0415489b82b3 · outbound
This paper cites On quadrature rules for solving Partial Differential Equations using Neural Networks.
Computational Math with Neural Networks is Hard On quadrature rules for solving Partial Differential Equations using Neural Networks
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:29.419545Z
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.
Observation 09b69af4-296f-4816-9fc0-5a8248bc495a · outbound
This paper cites A probabilistic algorithm for k-SAT and constraint satisfaction problems.
Computational Math with Neural Networks is Hard A probabilistic algorithm for k-SAT and constraint satisfaction problems
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:29.232881Z
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.
Observation ae8ef4f0-bf41-4174-8d78-ac725cde14a1 · outbound
This paper cites Deep solution operators for variational inequalities via proximal neural networks.
Computational Math with Neural Networks is Hard Deep solution operators for variational inequalities via proximal neural networks
Reference 44
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-07T14:51:23.996311Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9eee41d8-9f11-4bb1-a071-8ff478b1c456 · outbound
This paper cites Deep Operator Network Approximation Rates for Lipschitz Operators.
Computational Math with Neural Networks is Hard Deep Operator Network Approximation Rates for Lipschitz Operators
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:24.049918Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 59b5dc6d-e1ce-4269-a2b9-ce68913105be · outbound
This paper cites Deep learning in high dimension: neural network expression rates for analytic functions in L2(Rd, γd).
Computational Math with Neural Networks is Hard Deep learning in high dimension: neural network expression rates for analytic functions in L2(Rd, γd)
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:24.153165Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 06a01ec9-4026-4c92-8fe2-7aec67498b94 · outbound
This paper cites an unresolved cited work.
Computational Math with Neural Networks is Hard Unresolved cited work
Reference 47
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:51:29.081447Z
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.
Observation 5b4ba884-1b98-4092-96e1-8f1d7b52371e · outbound
This paper cites Le probl` eme de Dirichlet pour les ´ equations elliptiques du second ordre ` a coefficients discontinus.
Computational Math with Neural Networks is Hard Le probl` eme de Dirichlet pour les ´ equations elliptiques du second ordre ` a coefficients discontinus
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:28.898628Z
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.
Observation 26fb6330-e874-4d6e-88c5-c615d8d29e58 · outbound
This paper cites On the Complexity of Derivation in Propositional Calculus.
Computational Math with Neural Networks is Hard On the Complexity of Derivation in Propositional Calculus
Reference 49
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-07T14:51:28.686884Z
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.
Observation e594795c-c614-448e-a8a0-1ca4fd39b920 · outbound
This paper cites Weak adversarial networks for high-dimensional partial differ- ential equations.
Computational Math with Neural Networks is Hard Weak adversarial networks for high-dimensional partial differ- ential equations
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:51:28.504547Z
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.
Observation 3e47c877-116b-47a4-9515-d71ead372d29 · outbound
This paper cites an unresolved cited work.
Computational Math with Neural Networks is Hard Unresolved cited work
Reference 166
- Resolution
- verified exact
- doi, observed 2026-08-07T14:51:26.404584Z
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.
Observation 20bdce06-52d2-418a-ad45-be5589899974 · outbound
This paper cites an unresolved cited work.
Computational Math with Neural Networks is Hard Unresolved cited work
Reference 375
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:51:22.787521Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a2c5de12-c005-4bb2-af13-daa62d50f989 · outbound
This paper cites an unresolved cited work.
Computational Math with Neural Networks is Hard Unresolved cited work
Reference 1127
- Resolution
- verified exact
- doi, observed 2026-08-07T14:51:24.672116Z
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.
Observation 2e08f9da-eabc-49bc-bc13-aa083abf23a0 · outbound
This paper cites Towards optimal hierarchical training of neural networks.
Computational Math with Neural Networks is Hard Towards optimal hierarchical training of neural networks
Reference 2024
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-07T14:51:28.123104Z
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.
Pith citing papers
Observation aaf84f3c-6cc6-4dc2-8706-dcf73216b0a2 · inbound
Adaptive anisotropic composite quadratures for residual minimisation in neural PDE approximations cites this paper.
Adaptive anisotropic composite quadratures for residual minimisation in neural PDE approximations Computational Math with Neural Networks is Hard
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T15:36:08.149796Z
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.