Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-14T05:13:31.628201Z
Paper Citation Record · LEDGER
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs
As of 23 August 2026, this Paper Citation Record lists 77 of 77 outbound references and 0 inbound Pith citation observations for arXiv:1909.02449.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
77 of 77 outbound references displayed
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 1d570ab7-e4d8-4763-bb23-1ee1d2ffbe13 · outbound
This paper cites Distribution de la flore alpine dans le bassin des Dranses et dans quelques r ´egions voisines.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Distribution de la flore alpine dans le bassin des Dranses et dans quelques r ´egions voisines
Reference 1
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation aa827b04-1654-4bb6-a145-935555d49d04 · outbound
This paper cites Distance between sets.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Distance between sets
Reference 2
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation c19f0058-2008-4474-8392-da95b9913a0d · outbound
This paper cites Analytical redundancy and the design of robust failure detection systems.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Analytical redundancy and the design of robust failure detection systems
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:36.554196Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 8d05a6f0-36c5-43ea-9ad1-48578543de02 · outbound
This paper cites Finding structure in time.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Finding structure in time
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:36.464998Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation cb56e9b4-7af2-4c83-ac60-b1dc77534b72 · outbound
This paper cites Handbook of theoretical computer science.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Handbook of theoretical computer science
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:36.337458Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 687f05c5-2dd9-4d69-bde1-9e5a6f452055 · outbound
This paper cites Analytical redundancy methods in fault detection and isolation-survey and synthesis.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Analytical redundancy methods in fault detection and isolation-survey and synthesis
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:36.297148Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ca470b7e-130d-453d-a398-7cdbbb625bf6 · outbound
This paper cites Learning complex, extended se- quences using the principle of history compression.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Learning complex, extended se- quences using the principle of history compression
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:36.254968Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 6f1875d3-5c0e-485f-a5c8-38214b28f1d8 · outbound
This paper cites Detection of abrupt changes: theory and application.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Detection of abrupt changes: theory and application
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:36.123512Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ef351cab-23f7-45cc-a9a6-9b8d31ec8f5b · outbound
This paper cites Fundamentals of statistical signal pro- cessing.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Fundamentals of statistical signal pro- cessing
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:36.110713Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 3886cc5d-f23c-457f-8ec9-b25866a301f4 · outbound
This paper cites Integration of fault detection and di- agnosis methods.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Integration of fault detection and di- agnosis methods
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:36.057581Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation acbe0c25-efb4-4ac9-b0b1-d791a7909a22 · outbound
This paper cites Kernel smoothing.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Kernel smoothing
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:36.027132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 56f7d7d0-8c06-45af-aeb0-dc91961a1988 · outbound
This paper cites Optimal simulta- neous detection and estimation under a false alarm con- straint.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Optimal simulta- neous detection and estimation under a false alarm con- straint
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:35.936160Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation cda45e3c-af4e-4d63-b45c-9e5c8b532363 · outbound
This paper cites Phoneme recognition using time-delay neural networks.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Phoneme recognition using time-delay neural networks
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:35.896478Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a3ef3bbd-b885-4816-889d-c4b50ecc6684 · outbound
This paper cites Identification of faulty sensors using principal component analysis.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Identification of faulty sensors using principal component analysis
Reference 14
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 0d8ec076-ef7d-4a52-8dee-0ed2247cc2ef · outbound
This paper cites Long short- term memory.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Long short- term memory
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:35.761248Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a09a2a56-25c4-486c-b9d2-1fbca65c69ce · outbound
This paper cites Trends in the appli- cation of model-based fault detection and diagnosis of technical processes.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Trends in the appli- cation of model-based fault detection and diagnosis of technical processes
Reference 16
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation d1c3fe5d-d423-4510-86aa-b73420bc9d64 · outbound
This paper cites Serial order: A parallel distributed processing approach.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Serial order: A parallel distributed processing approach
Reference 17
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 1226ee07-bed2-445c-8ed2-519a71b61e2d · outbound
This paper cites A neural- network approach to fault detection and diagnosis in industrial processes.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs A neural- network approach to fault detection and diagnosis in industrial processes
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:35.504950Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 7d44ea6b-e92e-44d6-bb04-a54ca5b32f83 · outbound
This paper cites Robust detection and isolation of process faults using neural networks.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Robust detection and isolation of process faults using neural networks
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:35.457683Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ae3839b6-65eb-4841-974d-f53faff1be7c · outbound
This paper cites Distributed detection with multiple sensors: Part I-fundamentals.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Distributed detection with multiple sensors: Part I-fundamentals
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:35.443385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a546c75b-7313-408c-9033-8935a7d34aca · outbound
This paper cites Neural network based fault detection in robotic manipulators.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Neural network based fault detection in robotic manipulators
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:35.401399Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation d41a099d-8b70-4d9c-8eb8-7ed45e5e026b · outbound
This paper cites Fault diagnosis in chemical processes using Fisher discriminant analysis, discriminant partial least squares, and principal component analysis.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Fault diagnosis in chemical processes using Fisher discriminant analysis, discriminant partial least squares, and principal component analysis
Reference 22
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation b87dde1e-e861-4869-8930-8614ad30fcda · outbound
This paper cites Continuous emission monitoring.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Continuous emission monitoring
Reference 23
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 1aaf99a2-fe74-4e98-987c-50b0469ed4ef · outbound
This paper cites Di- agnosis techniques for sensor faults of industrial pro- cesses.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Di- agnosis techniques for sensor faults of industrial pro- cesses
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:35.161406Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 3c7daea0-79b3-4196-a300-c1ba256f94f3 · outbound
This paper cites Generalized contribution plots in multivariate statistical process monitoring.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Generalized contribution plots in multivariate statistical process monitoring
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:35.140398Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 54ed863b-ce58-4f88-9bd4-6fc5304c07e5 · outbound
This paper cites The elements of statistical learning.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs The elements of statistical learning
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:35.039044Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 0c210881-5626-4c47-81a1-30c88a72a186 · outbound
This paper cites Consistent dynamic PCA based on errors-in-variables subspace identification.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Consistent dynamic PCA based on errors-in-variables subspace identification
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:34.974474Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation fb833b7b-82d8-4283-9273-18e5323379d7 · outbound
This paper cites Proba- bility, random variables, and stochastic processes.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Proba- bility, random variables, and stochastic processes
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:34.939767Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 2485b590-e15d-48a5-bc93-1ef2b8b0b685 · outbound
This paper cites Novelty Detection: A Review — Part 1: Statistical Approaches.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Novelty Detection: A Review — Part 1: Statistical Approaches
Reference 29
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation f9074d26-7a09-480c-977f-21d18fba0d8b · outbound
This paper cites Model-based fault-detection and diagnosis–status and applications.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Model-based fault-detection and diagnosis–status and applications
Reference 30
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation f2182b0b-2e08-4d6d-abbc-b19ae70270a5 · outbound
This paper cites An improved PCA scheme for sensor FDI: Application to an air quality monitoring network.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs An improved PCA scheme for sensor FDI: Application to an air quality monitoring network
Reference 31
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 1a10157c-94a3-4bae-93c3-aeb29a23d769 · outbound
This paper cites Soft sensors for monitoring and control of industrial processes.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Soft sensors for monitoring and control of industrial processes
Reference 32
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 2b49f264-807b-4f88-be09-836e633692fc · outbound
This paper cites Application of computational intelligence for sensor fault detection and isolation.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Application of computational intelligence for sensor fault detection and isolation
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:34.518463Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation e43a4457-e4fc-4927-a469-e615690fb6f2 · outbound
This paper cites Multiple faults diagnosis for sensors in air handling unit using Fisher discrimi- nant analysis.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Multiple faults diagnosis for sensors in air handling unit using Fisher discrimi- nant analysis
Reference 34
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 365c01c1-4add-4b89-956d-782a8c2e05d6 · outbound
This paper cites Reconstruction-based contribution for process monitoring.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Reconstruction-based contribution for process monitoring
Reference 35
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a7f45a01-e5c4-4909-b6ff-83d8abd0f4b8 · outbound
This paper cites Estimation of faults in dc electrical power system.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Estimation of faults in dc electrical power system
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:34.233943Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 9db3e95e-d402-4585-98d2-cb1c2b26b3b8 · outbound
This paper cites Dis- tributed target detection in sensor networks using scan statistics.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Dis- tributed target detection in sensor networks using scan statistics
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:34.165855Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation c5812274-4f6a-4828-8eb1-b0d4244ba463 · outbound
This paper cites Sensor network data fault types.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Sensor network data fault types
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:34.150519Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 2191460c-e8d0-4d29-9701-6471d0609db1 · outbound
This paper cites Relaxed maximum a posteriori fault identification.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Relaxed maximum a posteriori fault identification
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:34.077401Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation fe828b3d-da13-4d6f-bd34-8b4091ab790d · outbound
This paper cites Tracking and data fusion.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Tracking and data fusion
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.948957Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a6e3c3b5-3e3d-40d8-b87e-0150ae6cd915 · outbound
This paper cites Scan statistics and applications.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Scan statistics and applications
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.855321Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 54325051-de69-4e21-bc4f-05b51aaabe8c · outbound
This paper cites Signal detection in non-Gaussian noise.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Signal detection in non-Gaussian noise
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.726613Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation cdc5ce9c-0e15-451a-ab05-8f918e4802bd · outbound
This paper cites Survey on data-driven industrial process monitoring and diagnosis.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Survey on data-driven industrial process monitoring and diagnosis
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.605614Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation bc3a0cf9-f565-4e61-8a31-0abb27e1a844 · outbound
This paper cites A knowledge-based system approach for sensor fault modeling, detection and mit- igation.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs A knowledge-based system approach for sensor fault modeling, detection and mit- igation
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.561718Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 656e49c9-972e-4f47-9a4e-b38018a581d3 · outbound
This paper cites Distributed detection and data fusion.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Distributed detection and data fusion
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.549456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 10452d22-179c-4e0b-9344-58271a1e98d7 · outbound
This paper cites Representation learning: A review and new perspec- tives.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Representation learning: A review and new perspec- tives
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.519995Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 9d52bf28-2eea-47c7-b443-452ffaf85815 · outbound
This paper cites Bootstrap inference for network construction with an application to a breast cancer microarray study.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Bootstrap inference for network construction with an application to a breast cancer microarray study
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.487854Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 8fd595e3-d15f-4b22-a01f-f99f745a86d0 · outbound
This paper cites An introduction to signal detection and estimation.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs An introduction to signal detection and estimation
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.367081Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation b1bb857c-612d-421b-94d8-35c7750ba185 · outbound
This paper cites Adaptive approximation for multiple sen- sor fault detection and isolation of nonlinear uncertain systems.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Adaptive approximation for multiple sen- sor fault detection and isolation of nonlinear uncertain systems
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.248768Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 7bce0ab7-0d87-4c9d-8fbc-bd270d37377a · outbound
This paper cites Sequential analysis: tests and confi- dence intervals.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Sequential analysis: tests and confi- dence intervals
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.175942Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation fa43cff1-2eff-4668-b999-2b12f7c449e0 · outbound
This paper cites Contribution plots for statistical process control: Analysis of the smearing-out effect.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Contribution plots for statistical process control: Analysis of the smearing-out effect
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.161891Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation d9d72775-0678-4ffb-b985-d6b320eaaa24 · outbound
This paper cites Sequential multi-sensor change-point detection.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Sequential multi-sensor change-point detection
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.149894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation f82d63a7-79b3-4a6d-9acb-8619d2869dbd · outbound
This paper cites A review on multi-label learning algorithms.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs A review on multi-label learning algorithms
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.110549Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 13297814-6517-4a61-9e08-f04677f6e6c8 · outbound
This paper cites On the Properties of Neural Machine Translation: Encoder-Decoder Approaches.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs On the Properties of Neural Machine Translation: Encoder-Decoder Approaches
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T05:13:30.904720Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 581e8fd5-137e-4885-a7f4-a10d1a94ab11 · outbound
This paper cites Towards end-to-end speech recognition with recurrent neural networks.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Towards end-to-end speech recognition with recurrent neural networks
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:33.009190Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 52c06f09-e304-48ba-b747-c88d47bc4749 · outbound
This paper cites Adam: A Method for Stochastic Optimization.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Adam: A Method for Stochastic Optimization
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T05:13:30.931085Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 464bbcea-bf9b-4fc9-8e1c-1095df8d9793 · outbound
This paper cites Sensor fault detection by sparsity optimization.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Sensor fault detection by sparsity optimization
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.955809Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 3613e8d4-3f38-4aa5-9f08-b531ec1c09ce · outbound
This paper cites Fault identification in distributed sensor networks based on universal probabilistic mod- eling.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Fault identification in distributed sensor networks based on universal probabilistic mod- eling
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.943420Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 41e22936-e7d9-43e1-a73e-31117e70a21f · outbound
This paper cites Distributed Fault Detection in Sensor Net- works using a Recurrent Neural Network.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Distributed Fault Detection in Sensor Net- works using a Recurrent Neural Network
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.930036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 699a3e51-cbc6-407e-9abb-ebac1b8a054f · outbound
This paper cites Data- driven control and process monitoring for industrial ap- plications—Part I.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Data- driven control and process monitoring for industrial ap- plications—Part I
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.873146Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 38b27b48-7417-48cc-9199-9da42dcae0cc · outbound
This paper cites Anomaly detection in ECG time signals via deep long short-term memory net- works.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Anomaly detection in ECG time signals via deep long short-term memory net- works
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.781107Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 09486d4a-2df9-46f2-a26a-48bb3902307f · outbound
This paper cites Fault isolation in data-driven multivariate process monitoring.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Fault isolation in data-driven multivariate process monitoring
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.711256Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 8ecfea6d-f2cb-4c52-a8bd-207d2cc8ae4a · outbound
This paper cites Change detection with an unknown sensor subset: More information is not always better.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Change detection with an unknown sensor subset: More information is not always better
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.625359Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation b844c445-b817-43e9-acbe-48ba8f34d15a · outbound
This paper cites Recurrent convolutional neural network for object recognition.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Recurrent convolutional neural network for object recognition
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.547850Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation fce0824e-41d7-48a4-99af-44b8a3876d93 · outbound
This paper cites Long Short Term Memory Networks for Anomaly Detection in Time Series.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Long Short Term Memory Networks for Anomaly Detection in Time Series
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.533855Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation fbb4a5bc-ad66-4bf1-b439-818beb7d0cb3 · outbound
This paper cites Industry 4.0: the industrial internet of things.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Industry 4.0: the industrial internet of things
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.477144Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 5acc69b5-a708-4b20-b51c-68e0a5815d73 · outbound
This paper cites Deep learning.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Deep learning
Reference 67
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T05:13:31.349651Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 25567d8f-257e-4422-8bbb-2bae49b324d3 · outbound
This paper cites Learning distance metrics for multi-label classifica- tion.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Learning distance metrics for multi-label classifica- tion
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.352064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 1d5d432f-e591-48f6-bc14-9603ebdce41a · outbound
This paper cites The Visual Object Tracking VOT2016 Challenge Results.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs The Visual Object Tracking VOT2016 Challenge Results
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.276318Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 0d1d52f7-6519-4dfc-b3e4-73f66ed2c3d3 · outbound
This paper cites LSTM-based Encoder-Decoder for Multi- sensor Anomaly Detection.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs LSTM-based Encoder-Decoder for Multi- sensor Anomaly Detection
Reference 70
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.263604Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation d657ef05-80ad-47c9-a3e8-3ef263bef825 · outbound
This paper cites Measurement, instru- mentation, and sensors handbook: spatial, mechanical, thermal, and radiation measurement.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Measurement, instru- mentation, and sensors handbook: spatial, mechanical, thermal, and radiation measurement
Reference 71
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.227461Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 5506bf22-ec69-452b-913f-699feda0d536 · outbound
This paper cites Assessment and testing of sensor validation algorithms IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 15 for environmental monitoring applications.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Assessment and testing of sensor validation algorithms IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 15 for environmental monitoring applications
Reference 72
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.159422Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation c3b9e5b0-751f-4022-9aa5-5b5f5d60fa84 · outbound
This paper cites Sensor Data Validation and Reconstruction.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Sensor Data Validation and Reconstruction
Reference 73
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.081676Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 90ae87ad-0951-417a-b71f-c4e94b57dff2 · outbound
This paper cites A KPI-based process monitoring and fault detection framework for large-scale processes.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs A KPI-based process monitoring and fault detection framework for large-scale processes
Reference 74
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:32.005632Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 025b84c4-f2a7-423a-8bea-2a7728749e12 · outbound
This paper cites A Sensor Fault-Resilient Framework for Predictive Emission Monitoring Sys- tems.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs A Sensor Fault-Resilient Framework for Predictive Emission Monitoring Sys- tems
Reference 75
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:31.967156Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 624df788-db8c-442c-bfae-3dcb7d4b4552 · outbound
This paper cites Disentangled ac- tivations in deep networks.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Disentangled ac- tivations in deep networks
Reference 76
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:31.893685Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation edc5c2f7-2821-4d54-bca8-572c24c7f90f · outbound
This paper cites Data-driven fault detection, isolation and estimation of aircraft gas turbine engine actuator and sensors.
A scalable algorithm for identifying multiple sensor faults using disentangled RNNs Data-driven fault detection, isolation and estimation of aircraft gas turbine engine actuator and sensors
Reference 77
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T05:13:31.773329Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Pith citing papers
No inbound Pith citation observations are available.