Paper Citation Record · LEDGER

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing

As of 16 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2501.02016.

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

pith.paper-citation-record.v1
2501.02016 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:34:53.045536Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

30 of 30 outbound references displayed

verified exact0
verified fuzzy19
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 82635327-b5b0-470c-9e23-cf022fc8aa0d · outbound

This paper cites Dual attention-based encoder–decoder: A customized sequence-to-sequence learning for soft sensor development,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Dual attention-based encoder–decoder: A customized sequence-to-sequence learning for soft sensor development,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.490239Z

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 4f690852-4d71-446b-af8f-a226c056b423 · outbound

This paper cites Virtual sensor development for mul- tioutput nonlinear processes based on bilinear neighborhood preserving regression model with localized construction,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Virtual sensor development for mul- tioutput nonlinear processes based on bilinear neighborhood preserving regression model with localized construction,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.475158Z

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 7c4c4df6-0c6a-477d-9613-c1e7aaedceed · outbound

This paper cites A review on soft sensors for monitoring, control, and optimization of industrial processes,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing A review on soft sensors for monitoring, control, and optimization of industrial processes,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.459920Z

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 676916c8-dc49-4898-91a7-43e27da8c79c · outbound

This paper cites A zero-shot soft sensor modeling approach using adversarial learning for robustness against sensor fault,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing A zero-shot soft sensor modeling approach using adversarial learning for robustness against sensor fault,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T22:34:52.817546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11c2514a-f2fd-4ffe-a18f-dac3aee65362 · outbound

This paper cites Data-driven soft sensors in the process industry,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Data-driven soft sensors in the process industry,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T22:34:52.932437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b74d1888-ce4e-4aa8-b884-115bcc42f102 · outbound

This paper cites Consistent-contrastive network with temporality-awareness for robust-to-anomaly industrial soft sensor,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Consistent-contrastive network with temporality-awareness for robust-to-anomaly industrial soft sensor,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T22:34:52.937210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b45702c-f1d9-49d7-85fb-85c80c80b869 · outbound

This paper cites Soft sensor modeling method based on target-guided related feature learning and its application,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Soft sensor modeling method based on target-guided related feature learning and its application,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.413503Z

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 8ab43281-974e-4d58-bafe-d56409f82dd9 · outbound

This paper cites A survey on deep learning for data-driven soft sensors,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing A survey on deep learning for data-driven soft sensors,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T22:34:52.946586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35a8ffe2-188c-4b2f-876f-67b766f07aaa · outbound

This paper cites Deep learning- based feature representation and its application for soft sensor modeling with variable-wise weighted sae,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Deep learning- based feature representation and its application for soft sensor modeling with variable-wise weighted sae,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.387282Z

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 39c3cca3-0043-4e0e-b701-c182226aa4d1 · outbound

This paper cites Gated stacked target-related autoencoder: A novel deep feature extraction and layerwise ensemble method for industrial soft sensor application,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Gated stacked target-related autoencoder: A novel deep feature extraction and layerwise ensemble method for industrial soft sensor application,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T22:34:52.955096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8816d310-4cfd-4f26-a44b-7d65986cd12a · outbound

This paper cites Grassnet: Graph soft sensing neural networks,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Grassnet: Graph soft sensing neural networks,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.362219Z

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 29218aec-92e1-4854-8d78-de688c2dc110 · outbound

This paper cites Domain adaptation graph convolution network for quality inferring of batch processes,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Domain adaptation graph convolution network for quality inferring of batch processes,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.347485Z

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 3d2995ec-ac09-4146-aa7e-0fee9d8acd8c · outbound

This paper cites Multichannel diffusion graph convolutional network for the prediction of endpoint composition in the converter steelmaking process,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Multichannel diffusion graph convolutional network for the prediction of endpoint composition in the converter steelmaking process,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T22:34:52.968584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26c9e0ed-f806-40ee-9de4-b779a4cc71d2 · outbound

This paper cites Soft sensor-based deep temporal-graph convolutional network for applications in human motion tracking,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Soft sensor-based deep temporal-graph convolutional network for applications in human motion tracking,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.318801Z

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 53981fe3-b45b-4891-92cd-4cae6e9a9b77 · outbound

This paper cites Dynamic graph-based adaptive learning for online industrial soft sensor with mutable spatial coupling relations,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Dynamic graph-based adaptive learning for online industrial soft sensor with mutable spatial coupling relations,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.302506Z

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 33856169-4805-453e-b5ef-716d79ca3418 · outbound

This paper cites Deep graph network for process soft sensor development,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Deep graph network for process soft sensor development,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.283824Z

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 94fdbc97-bf64-40d2-86a0-8712287a20f3 · outbound

This paper cites Multi-source unsupervised soft sensor based on joint distribution alignment and mapping structure preservation,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Multi-source unsupervised soft sensor based on joint distribution alignment and mapping structure preservation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.268078Z

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 165d4491-13b4-4674-aed0-3160979da969 · outbound

This paper cites Multisensor fusion on hyper- graph for fault diagnosis,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Multisensor fusion on hyper- graph for fault diagnosis,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.253556Z

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 6c3acbda-4eb5-4538-905b-e05e7902bc62 · outbound

This paper cites Temporal multi-resolution hypergraph attention network for remaining useful life prediction of rolling bearings,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Temporal multi-resolution hypergraph attention network for remaining useful life prediction of rolling bearings,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.239489Z

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 edbe2379-ce8e-49b9-864f-b1f9090205d1 · outbound

This paper cites Industrial time series determi- native anomaly detection based on constraint hypergraph,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Industrial time series determi- native anomaly detection based on constraint hypergraph,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.224906Z

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 f9021edb-6388-420b-bf3f-6d8e3221f043 · outbound

This paper cites Mlp-mixer: An all-mlp architecture for vision,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Mlp-mixer: An all-mlp architecture for vision,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T22:34:53.004098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 326fce17-069e-4e76-88c9-71296127b23c · outbound

This paper cites Deep residual learning for image recognition,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Deep residual learning for image recognition,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T22:34:53.008387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb9287b6-49a5-4f9f-8934-0ac8590bf134 · outbound

This paper cites Learning with hypergraphs: Clus- tering, classification, and embedding,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Learning with hypergraphs: Clus- tering, classification, and embedding,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.187382Z

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 f31052ff-1af8-482a-9a99-691e3796cd5e · outbound

This paper cites Hypergraph neural net- works,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Hypergraph neural net- works,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T22:34:53.017213Z

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Unavailable: canonical work link unavailable.

Observation f9ae8a53-efd6-47f8-8732-83736d5a30e1 · outbound

This paper cites Robust data-driven soft sensor based on iteratively weighted least squares support vector regression optimized by the cuckoo optimization algorithm,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Robust data-driven soft sensor based on iteratively weighted least squares support vector regression optimized by the cuckoo optimization algorithm,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.162235Z

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 846503e9-4357-4b8c-aec2-bca7b9d43431 · outbound

This paper cites Soft-sensing model development using plsr-based dynamic extreme learning machine with an enhanced hidden layer,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Soft-sensing model development using plsr-based dynamic extreme learning machine with an enhanced hidden layer,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T22:34:53.027215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d357ce71-a076-49b7-b849-82cdd80c7d8c · outbound

This paper cites A data-driven soft sensor based on multilayer perceptron neural network with a double lasso approach,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing A data-driven soft sensor based on multilayer perceptron neural network with a double lasso approach,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.136582Z

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 99092dfe-f7b8-42f6-aa73-769018f54a2e · outbound

This paper cites Graph convolutional network soft sensor for process quality prediction,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Graph convolutional network soft sensor for process quality prediction,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.120543Z

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 77c01fdc-1c77-4f5b-9054-92f27c34a675 · outbound

This paper cites Statistical process monitoring of a multiphase flow facility,.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Statistical process monitoring of a multiphase flow facility,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:34:53.103461Z

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 1ee06369-eb8b-4f76-b82a-e0964320b913 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Adam: A Method for Stochastic Optimization

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T22:34:53.045536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.