Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T17:23:49.307429Z
Paper Citation Record · LEDGER
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes
As of 16 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 1 inbound Pith citation observation for arXiv:2507.11178.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:18:49.948480Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T15:18:53.068505Z
Reference resolution
27 of 27 outbound references displayed
- verified exact0
- verified fuzzy26
- unresolved1
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- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation f81d2182-40e2-4079-869e-1025a559ac1e · outbound
This paper cites Regioselective hydroformylation of propene catalysed by rhodium-zeolite,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Regioselective hydroformylation of propene catalysed by rhodium-zeolite,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:52.973579Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d79f06af-bedb-434e-ab08-c1d0595dfd7b · outbound
This paper cites Causal-trivial attention graph neural network for fault diagnosis of complex industrial processes,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Causal-trivial attention graph neural network for fault diagnosis of complex industrial processes,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:52.838926Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d063b0ef-9c29-4948-a259-5e83e352326a · outbound
This paper cites Investigating causal relations by econometric models and cross-spectral methods,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Investigating causal relations by econometric models and cross-spectral methods,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:52.694177Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c3f9d239-5611-432f-8122-69d58be44348 · outbound
This paper cites An integrated distributed fault diagnosis framework for large-scale industrial processes based on spatio–temporal causal analysis,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes An integrated distributed fault diagnosis framework for large-scale industrial processes based on spatio–temporal causal analysis,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:52.527483Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 40168e5c-6ef8-4f81-8c71-fbc8897ae58a · outbound
This paper cites Attribution-aided non- linear granger causality discovery method and its industrial application,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Attribution-aided non- linear granger causality discovery method and its industrial application,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:52.399440Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8c316960-5bb6-4bf5-8bf2-19eb38243288 · outbound
This paper cites Causal inference for time series,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Causal inference for time series,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:52.245704Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 38690283-2231-47fa-9aea-80a5080e340d · outbound
This paper cites A spatiotemporal causal model for revealing developmen- tal changes in infants’ brain effective connectivity networks during the first year of life,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes A spatiotemporal causal model for revealing developmen- tal changes in infants’ brain effective connectivity networks during the first year of life,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:52.120889Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6f6a4eab-ed7f-4392-8851-a8ed6fd901e4 · outbound
This paper cites Neural granger causality,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Neural granger causality,
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:23:47.520774Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 062a52ec-1e13-44a4-8102-8c217773a8ed · outbound
This paper cites Economy statistical recurrent units for inferring nonlinear granger causality,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Economy statistical recurrent units for inferring nonlinear granger causality,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:51.917444Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ded67a56-5288-49d9-bd13-358bc3c08d65 · outbound
This paper cites Cuts: Neural causal discovery from irregular time-series data,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Cuts: Neural causal discovery from irregular time-series data,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:51.790895Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation dc3b9adc-66d1-4add-a7ee-563d092887da · outbound
This paper cites Granger causality using jacobian in neural networks,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Granger causality using jacobian in neural networks,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:51.673845Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b4bbed99-4897-487f-b55c-d6a6eaaee222 · outbound
This paper cites Cuts+: High- dimensional causal discovery from irregular time-series,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Cuts+: High- dimensional causal discovery from irregular time-series,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:51.530695Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e4105eff-c310-4fa5-b22b-b121e537532c · outbound
This paper cites Neural additive vector autoregres- sion models for causal discovery in time series,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Neural additive vector autoregres- sion models for causal discovery in time series,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:51.401469Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1ac1cb3d-d2be-4745-8adc-e128a31a018f · outbound
This paper cites Causal discovery with attention- based convolutional neural networks,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Causal discovery with attention- based convolutional neural networks,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:51.259415Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation cbc597a9-f43b-4d58-be8f-b221f48b1467 · outbound
This paper cites Interpretable models for granger causal- ity using self-explaining neural networks,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Interpretable models for granger causal- ity using self-explaining neural networks,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:51.139256Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2abdb047-eae2-4911-b5d5-cc7e7bb2591f · outbound
This paper cites Causal recurrent variational autoencoder for medical time series generation,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Causal recurrent variational autoencoder for medical time series generation,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:50.991127Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 793bdfd4-d3d0-4c91-a241-974fad8a1eec · outbound
This paper cites An information- theoretic approach for heterogeneous differentiable causal discovery,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes An information- theoretic approach for heterogeneous differentiable causal discovery,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:50.845673Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b7576e2d-b0e9-480a-a01e-b0c830932fbb · outbound
This paper cites Causality detection with matrix-based transfer entropy,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Causality detection with matrix-based transfer entropy,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:50.742566Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 81a77687-e6df-4412-8a07-5b9d6bda4ca6 · outbound
This paper cites Surrogates with random fourier phases,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Surrogates with random fourier phases,
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:50.589571Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 75f795ed-da4d-4074-96c4-338f9a21cbc2 · outbound
This paper cites Detection of the number of signals using the benjamini-hochberg procedure,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Detection of the number of signals using the benjamini-hochberg procedure,
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:50.430039Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0b6f4d02-7a3b-4c6f-9e79-14cc6fbe302d · outbound
This paper cites Dream3: network inference using dynamic context likelihood of relatedness and the inferelator,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Dream3: network inference using dynamic context likelihood of relatedness and the inferelator,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:50.288066Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e25eb821-31fb-4b0e-b510-a475da27b26e · outbound
This paper cites Extensive chaos in the lorenz-96 model,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Extensive chaos in the lorenz-96 model,
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:50.138844Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f1606899-da17-471c-aaf1-47f5ab2a69b5 · outbound
This paper cites Causaltime: Realistically generated time-series for benchmarking of causal discov- ery,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Causaltime: Realistically generated time-series for benchmarking of causal discov- ery,
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:50.014412Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation aebb11e1-e770-418c-aaeb-a6c09bfcfa93 · outbound
This paper cites Jacobian regularizer- based neural granger causality,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Jacobian regularizer- based neural granger causality,
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:49.884445Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 991a2843-daba-4ae3-8daf-a359fa8a443e · outbound
This paper cites Base control for the tennessee eastman problem,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Base control for the tennessee eastman problem,
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:49.755403Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 05651d86-f0d2-4429-9d62-d16102b7d171 · outbound
This paper cites Cipcad-bench: Continuous industrial process datasets for benchmarking causal discovery methods,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Cipcad-bench: Continuous industrial process datasets for benchmarking causal discovery methods,
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:49.620802Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation cf1165d6-a660-4ca6-8d24-89da741da345 · outbound
This paper cites Soft sensors for product quality monitoring in debutanizer distillation columns,.
A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes Soft sensors for product quality monitoring in debutanizer distillation columns,
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T17:23:49.483396Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
Observation f4b4a320-8f48-4c8c-890a-3f6620ea545d · inbound
SFNet: A Spatial-Frequency Domain Deep Learning Network for Efficient Alzheimer's Disease Diagnosis cites this paper.
SFNet: A Spatial-Frequency Domain Deep Learning Network for Efficient Alzheimer's Disease Diagnosis A Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes
Reference 14
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-06T15:18:53.132218Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.