Paper Citation Record · LEDGER

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs

As of 21 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 3 inbound Pith citation observations for arXiv:2505.23702.

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

pith.paper-citation-record.v1
2505.23702 v1

Coverage vector

measured 53 of 53 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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

Source: pith, observed 2026-07-08T16:55:08.391283Z

Reference resolution

53 of 53 outbound references displayed

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External citation measurements

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Outbound references

Observation b56cde09-68b0-449f-8cb9-4eb4afa5bedd · outbound

This paper cites American Mathematical Society, 2022.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs American Mathematical Society, 2022

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T12:48:53.969539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8c313ef-df52-4326-b71b-3b1a07e8bf5a · outbound

This paper cites Cam- bridge university press, 2002.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Cam- bridge university press, 2002

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:12.282967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f523ab33-807a-4d15-912f-a86e1a79f012 · outbound

This paper cites Hyperbolic systems of conservation laws ii.Communications on Pure and Applied Mathematics, 10(4):537–566, 1957.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Hyperbolic systems of conservation laws ii.Communications on Pure and Applied Mathematics, 10(4):537–566, 1957

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:11.934337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6a5220ca-13e1-4ed4-afeb-9d27e2096484 · outbound

This paper cites Lax–hopf based incorporation of internal boundary conditions into hamilton–jacobi equation.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Lax–hopf based incorporation of internal boundary conditions into hamilton–jacobi equation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:11.575605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fd9c3e3f-ef0a-4cbb-b3e3-710014a94af5 · outbound

This paper cites Lax–hopf based incorporation of internal boundary conditions into hamilton-jacobi equation.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Lax–hopf based incorporation of internal boundary conditions into hamilton-jacobi equation

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:11.303358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1ea281ea-9864-4871-9a3e-59a6310eaa33 · outbound

This paper cites A discontinuous galerkin finite element method for hamilton–jacobi equations.SIAM Journal on Scientific computing, 21(2):666–690, 1999.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs A discontinuous galerkin finite element method for hamilton–jacobi equations.SIAM Journal on Scientific computing, 21(2):666–690, 1999

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:11.025160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8229cac4-fb21-4143-aaf8-33f4cb8b66cc · outbound

This paper cites The initial value problem for nonlinear hyperbolic equations in two independent variables.Ann.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs The initial value problem for nonlinear hyperbolic equations in two independent variables.Ann

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:10.661640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9c85c426-9c8b-40c9-8879-8035ba0c6642 · outbound

This paper cites A finite difference method for the computation of discontinuous solutions of the equations of fluid dynamics.Sbornik: Mathematics, 47(8-9):357–393, 1959.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs A finite difference method for the computation of discontinuous solutions of the equations of fluid dynamics.Sbornik: Mathematics, 47(8-9):357–393, 1959

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:10.364096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b4066e68-c6e4-4b1d-8b08-0e0573dac437 · outbound

This paper cites High order eno and weno schemes for computational fluid dynamics.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs High order eno and weno schemes for computational fluid dynamics

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:10.085387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 976e7d01-ad57-4e84-aaed-3727a09cd677 · outbound

This paper cites Weighted essentially non-oscillatory schemes.Journal of computational physics, 115(1):200–212, 1994.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Weighted essentially non-oscillatory schemes.Journal of computational physics, 115(1):200–212, 1994

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:09.777318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8594c225-d585-4337-89d5-281a10097ba2 · outbound

This paper cites The local discontinuous galerkin method for time-dependent convection-diffusion systems.SIAM Journal on Numerical Analysis, 35 (6):2440–2463, 1998.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs The local discontinuous galerkin method for time-dependent convection-diffusion systems.SIAM Journal on Numerical Analysis, 35 (6):2440–2463, 1998

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:09.532300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 78a5a871-5104-4d0f-a0ab-8d499d02395c · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Fourier Neural Operator for Parametric Partial Differential Equations

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:48:55.456494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 268dd88a-c0fe-4fda-8fee-66a749c62a44 · outbound

This paper cites Learning nonlinear operators via deeponet based on the universal approximation theorem of operators.Nature machine intelligence, 3(3):218–229, 2021.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Learning nonlinear operators via deeponet based on the universal approximation theorem of operators.Nature machine intelligence, 3(3):218–229, 2021

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T12:48:55.563815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 856a6741-ac7c-4a1e-8389-4add43355dbe · outbound

This paper cites Convolutional networks for images, speech, and time series.The handbook of brain theory and neural networks, 3361(10):1995, 1995.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Convolutional networks for images, speech, and time series.The handbook of brain theory and neural networks, 3361(10):1995, 1995

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T12:48:55.566844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23099166-7f0a-49d2-a9a7-a2463560c11a · outbound

This paper cites Geometric deep learning: going beyond euclidean data.IEEE Signal Processing Magazine, 34(4):18–42, 2017.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Geometric deep learning: going beyond euclidean data.IEEE Signal Processing Magazine, 34(4):18–42, 2017

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:09.269568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b4b59c4f-4aed-4f79-a536-3a8ace2ac6d5 · outbound

This paper cites Characterizing possible failure modes in physics-informed neural networks.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Characterizing possible failure modes in physics-informed neural networks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T12:48:55.573015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfac2d0a-91d7-4e1c-9f8b-691aa73db4ec · outbound

This paper cites Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T12:48:55.617261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c372d24a-d049-4635-ac8a-3dfff0f68210 · outbound

This paper cites an unresolved cited work.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T12:48:55.680622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eaa275a8-2ea2-4361-bfb6-066ca5a07708 · outbound

This paper cites an unresolved cited work.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T12:48:55.827965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddc66daa-3280-44e5-8e1b-c475d751d346 · outbound

This paper cites Understanding the behaviour of contrastive loss.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Understanding the behaviour of contrastive loss

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:08.963043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f8fad323-8c8b-4104-a390-a82600a4a82f · outbound

This paper cites Limitations of physics informed machine learning for nonlinear two-phase transport in porous media.Journal of Machine Learning for Modeling and Computing, 1(1), 2020.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Limitations of physics informed machine learning for nonlinear two-phase transport in porous media.Journal of Machine Learning for Modeling and Computing, 1(1), 2020

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T12:48:56.035751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53218b02-0faf-4530-8092-ffea89899e12 · outbound

This paper cites wpinns: Weak physics informed neural networks for approximating entropy solutions of hyperbolic conservation laws.SIAM Journal on Numerical Analysis, 62(2):811–841, 2024.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs wpinns: Weak physics informed neural networks for approximating entropy solutions of hyperbolic conservation laws.SIAM Journal on Numerical Analysis, 62(2):811–841, 2024

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:08.694942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5d80522e-33df-401d-819c-3669b285fc62 · outbound

This paper cites Ppinn: Parareal physics-informed neural network for time-dependent pdes.Computer Methods in Applied Mechanics and Engineering, 370:113250, 2020.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Ppinn: Parareal physics-informed neural network for time-dependent pdes.Computer Methods in Applied Mechanics and Engineering, 370:113250, 2020

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T12:48:56.233696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d4b9601-bad0-4998-97b1-9031da215442 · outbound

This paper cites an unresolved cited work.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Unresolved cited work

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T12:48:56.359245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 895de784-3d8d-4c2d-a54b-86520299a02c · outbound

This paper cites Enhanced fifth order weno shock-capturing schemes with deep learning.Results in Applied Mathematics, 12: 100201, 2021.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Enhanced fifth order weno shock-capturing schemes with deep learning.Results in Applied Mathematics, 12: 100201, 2021

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:08.372097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ce6b1698-51bd-467e-bba8-e7b3b7246b46 · outbound

This paper cites Roenet: Predicting discontinuity of hyperbolic systems from continuous data.International Journal for Numerical Methods in Engineering, 125(6):e7406, 2024.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Roenet: Predicting discontinuity of hyperbolic systems from continuous data.International Journal for Numerical Methods in Engineering, 125(6):e7406, 2024

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:08.064543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 85221ce1-5912-4845-83db-487c14825455 · outbound

This paper cites On kinematic waves i.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs On kinematic waves i

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:07.789733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3ad81b7c-6e95-4e74-86b2-6e6b2f629474 · outbound

This paper cites an unresolved cited work.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:49:07.516522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 408fd8d9-0f56-46de-81cc-304edb8ab57e · outbound

This paper cites A study of traffic capacity.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs A study of traffic capacity

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:07.200483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 897defe8-217e-4bfc-9383-03dc9891ca31 · outbound

This paper cites Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings.Transportation Research Part B: Methodological, 42(9):759–770, 2008.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings.Transportation Research Part B: Methodological, 42(9):759–770, 2008

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:06.899074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0fc27e68-758e-4bf5-844f-4e9495f680ac · outbound

This paper cites Properties of a well-defined macroscopic fundamental diagram for urban traffic.Transportation Research Part B: Methodological, 45(3): 605–617, 2011.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Properties of a well-defined macroscopic fundamental diagram for urban traffic.Transportation Research Part B: Methodological, 45(3): 605–617, 2011

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:06.620244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bbf8ab36-7020-49cd-926f-502454c03869 · outbound

This paper cites An analysis of traffic flow.Operations research, 7(1):79–85, 1959.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs An analysis of traffic flow.Operations research, 7(1):79–85, 1959

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:06.338801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 27de3847-b7ed-4b5e-ba50-89be31da2f30 · outbound

This paper cites Speed, volume and density relationships.Quality and theory of traffic flow, 1961.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Speed, volume and density relationships.Quality and theory of traffic flow, 1961

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:06.058613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2dad0960-1caf-4f93-8b12-159f30660cb4 · outbound

This paper cites an unresolved cited work.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:49:05.773339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 36108a55-42d7-4bb4-8d75-53b59b493b3a · outbound

This paper cites A fractional burgers equation arising in nonlinear acoustics: theory and numerics.IFAC Proceedings Volumes, 46(23): 406–411, 2013.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs A fractional burgers equation arising in nonlinear acoustics: theory and numerics.IFAC Proceedings Volumes, 46(23): 406–411, 2013

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:05.484071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6f43f6fd-8bf6-4dfd-996e-238ee989005c · outbound

This paper cites an unresolved cited work.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:49:05.240032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5bb55184-7170-4c3d-8bc9-14d3446467bf · outbound

This paper cites Traffic current fluctuation and the burgers equation.Japanese journal of applied physics, 17(5):811, 1978.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Traffic current fluctuation and the burgers equation.Japanese journal of applied physics, 17(5):811, 1978

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:04.928113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fbf4bb42-f0f1-46ab-8ee2-741dc5572e59 · outbound

This paper cites Notes on the burgers equation.University of Marylan, 2011.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Notes on the burgers equation.University of Marylan, 2011

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:04.662815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1f830e00-4d31-467d-a7a8-7f40a8d67698 · outbound

This paper cites an unresolved cited work.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:49:04.357843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a575e4e2-0617-4b91-9295-d8cafa042443 · outbound

This paper cites second order.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs second order

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:04.039720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b903a8a5-5376-4340-ba77-6cdd8a26c986 · outbound

This paper cites Structural properties of solutions arising from a nonequilibrium traffic flow theory.Transportation Research Part B: Methodological, 34(7):583–603, 2000.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Structural properties of solutions arising from a nonequilibrium traffic flow theory.Transportation Research Part B: Methodological, 34(7):583–603, 2000

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:03.765748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fd2f447f-d218-4373-a097-c10f70d53f29 · outbound

This paper cites I-24 motion: An instrument for freeway traffic science.Transportation Research Part C: Emerging Technologies, 155: 104311, 2023.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs I-24 motion: An instrument for freeway traffic science.Transportation Research Part C: Emerging Technologies, 155: 104311, 2023

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:03.479515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3a36d335-cf77-49fb-b7cf-21a27dfceacd · outbound

This paper cites So you think you can track?.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs So you think you can track?

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:49:00.584005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5c2bca6b-87b2-49e3-9912-bdb1863d3a0f · outbound

This paper cites Automatic vehicle trajectory data reconstruction at scale.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Automatic vehicle trajectory data reconstruction at scale

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:49:00.303496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 359a7ada-0e42-4f2a-8012-044ff2ce8d83 · outbound

This paper cites Afinitedifferencemethodforthenumericalcomputationofdiscontinuous solutions of the equations of fluid dynamics.Mathematicheckii Sbornik, 47:271–290, 1959.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Afinitedifferencemethodforthenumericalcomputationofdiscontinuous solutions of the equations of fluid dynamics.Mathematicheckii Sbornik, 47:271–290, 1959

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:03.198116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3b02b42c-c70d-4ffe-a289-908141ea87cb · outbound

This paper cites One-sided difference approximations for nonlinear conservation laws.Mathematics of Computation, 36(154):321–351, 1981.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs One-sided difference approximations for nonlinear conservation laws.Mathematics of Computation, 36(154):321–351, 1981

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:02.891964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2245a6dc-787d-4c21-8e1f-e9d1deae95f5 · outbound

This paper cites second order.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs second order

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:02.564365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b6980412-0356-463a-8cda-2e33e337719b · outbound

This paper cites A non-equilibrium traffic model devoid of gas-like behavior.Trans- portation Research Part B: Methodological, 36(3):275–290, 2002.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs A non-equilibrium traffic model devoid of gas-like behavior.Trans- portation Research Part B: Methodological, 36(3):275–290, 2002

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:02.280315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 35bb0dfa-fdd2-4ef7-92c9-26aa4a1850ff · outbound

This paper cites Parsing gigabytes of json per second.The VLDB Journal, 28(6):941–960, 2019.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Parsing gigabytes of json per second.The VLDB Journal, 28(6):941–960, 2019

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:02.064935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 76f47133-131f-46fa-8d01-d6f63b69e83b · outbound

This paper cites an unresolved cited work.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Unresolved cited work

Reference 50

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:49:01.794123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6ab36ab9-2ffa-4226-b9f0-e3e914fa81f7 · outbound

This paper cites •Otherwise, choose the stencil{f + i−1, f+ i }.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs •Otherwise, choose the stencil{f + i−1, f+ i }

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:01.487508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 46ce6d39-679e-4086-9e2f-512d8ee08bf1 · outbound

This paper cites A similar approach is applied to computeˆf − i+ 1 2 using the right-biased stencil.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs A similar approach is applied to computeˆf − i+ 1 2 using the right-biased stencil

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:01.226932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 073c6735-b1a4-4de8-b4b9-8e20a787c8e3 · outbound

This paper cites Each time step is represented as a separate input channel, for a total ofb input channels.

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs Each time step is represented as a separate input channel, for a total ofb input channels

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:49:00.921538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation ca766179-5ae8-4ecd-ab98-b04801776fd7 · inbound

Conservative Discrete Structure Stabilizes Autoregressive Rollouts in a 1D Drift Diffusion Poisson Benchmark cites this paper.

Conservative Discrete Structure Stabilizes Autoregressive Rollouts in a 1D Drift Diffusion Poisson Benchmark (U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:56:16.002287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 81545985-36d3-460f-a927-8d2e37a7cbe7 · inbound

Mass-Conserving Physics-Informed Neural Networks For The One-Dimensional Advection-Diffusion Equation cites this paper.

Mass-Conserving Physics-Informed Neural Networks For The One-Dimensional Advection-Diffusion Equation (U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-07-08T16:55:08.392535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 08c9688a-dd3a-4559-a415-c89cfa1e2fe7 · inbound

Guarantees by Construction for Learned Finite Volume Schemes on Steady Supersonic Flow cites this paper.

Guarantees by Construction for Learned Finite Volume Schemes on Steady Supersonic Flow (U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T10:40:36.511814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.