Gaussian Processes in Power Systems: Techniques, Applications, and Future Works | Paper Citation Record

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This paper cites A review of current challenges and trends in energy systems modeling,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works A review of current challenges and trends in energy systems modeling,

Reference 1

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This paper cites Reinforcement learning and its applications in modern power and energy systems: A review,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Reinforcement learning and its applications in modern power and energy systems: A review,

Reference 2

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This paper cites Support vector machines,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Support vector machines,

Reference 3

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This paper cites Transformer in transformer,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Transformer in transformer,

Reference 4

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This paper cites Deep Gaussian Processes: A Survey.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Deep Gaussian Processes: A Survey

Reference 5

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Reference 6

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Reference 7

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This paper cites Beyond Intuition, a Framework for Applying GPs to Real-World Data.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Beyond Intuition, a Framework for Applying GPs to Real-World Data

Reference 8

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This paper cites Local and global sparse Gaussian process approximations,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Local and global sparse Gaussian process approximations,

Reference 9

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This paper cites Learning Power Flow with Confidence: A Probabilistic Guarantee Framework for Voltage Risk.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Learning Power Flow with Confidence: A Probabilistic Guarantee Framework for Voltage Risk

Reference 10

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Reference 11

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This paper cites Kernel interpolation for scalable struc- tured Gaussian processes (KISS-GP),.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Kernel interpolation for scalable struc- tured Gaussian processes (KISS-GP),

Reference 12

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This paper cites Deep kernel learning,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Deep kernel learning,

Reference 13

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This paper cites GPflow: A Gaussian process library using TensorFlow,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works GPflow: A Gaussian process library using TensorFlow,

Reference 14

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This paper cites Gpytorch: Blackbox matrix-matrix Gaussian process inference with gpu acceleration,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Gpytorch: Blackbox matrix-matrix Gaussian process inference with gpu acceleration,

Reference 15

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This paper cites BoTorch: A framework for efficient Monte- Carlo Bayesian optimization,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works BoTorch: A framework for efficient Monte- Carlo Bayesian optimization,

Reference 16

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This paper cites Power load probability density forecasting using Gaussian process quantile regression,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Power load probability density forecasting using Gaussian process quantile regression,

Reference 17

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This paper cites Review on probabilistic forecasting of wind power generation,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Review on probabilistic forecasting of wind power generation,

Reference 18

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This paper cites Short-term electric load pre- diction in smart grid using multi-output Gaussian processes regression,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Short-term electric load pre- diction in smart grid using multi-output Gaussian processes regression,

Reference 19

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This paper cites Anaya-Lara, N.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Anaya-Lara, N

Reference 20

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This paper cites Review of load forecasting based on artificial intelligence methodologies, models, and challenges,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Review of load forecasting based on artificial intelligence methodologies, models, and challenges,

Reference 21

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Observation 85fcd2d1-119f-4671-b04c-155c853dde5f · outbound

This paper cites Short- term residential load forecasting based on LSTM recurrent neural network,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Short- term residential load forecasting based on LSTM recurrent neural network,

Reference 22

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Observation 62b663a5-3d94-4e20-aab5-2e2d1dd4718c · outbound

This paper cites Short-term load forecasting for community battery systems based on temporal convolutional networks,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Short-term load forecasting for community battery systems based on temporal convolutional networks,

Reference 23

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This paper cites A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids,

Reference 24

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This paper cites Short-term load forecasting based on a semi-parametric additive model,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Short-term load forecasting based on a semi-parametric additive model,

Reference 25

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This paper cites A hybrid approach based on the Gaussian process with t-observation model for short-term wind speed forecasts,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works A hybrid approach based on the Gaussian process with t-observation model for short-term wind speed forecasts,

Reference 27

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Observation ca54caf7-ff25-49e4-a4fe-0d9a5b4c6f05 · outbound

This paper cites Short-term wind speed prediction using empirical wavelet transform and Gaussian process regression,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Short-term wind speed prediction using empirical wavelet transform and Gaussian process regression,

Reference 28

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This paper cites Forecasting of daily global solar radiation using wavelet transform-coupled Gaussian process re- gression: Case study in spain,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Forecasting of daily global solar radiation using wavelet transform-coupled Gaussian process re- gression: Case study in spain,

Reference 29

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Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Wavelet-Gaussian process regression model for forecasting daily solar radiation in the saharan climate,

Reference 30

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This paper cites PV power forecasting using an integrated GA-PSO-ANFIS approach and Gaussian process regression based feature selection strategy,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works PV power forecasting using an integrated GA-PSO-ANFIS approach and Gaussian process regression based feature selection strategy,

Reference 31

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This paper cites Wind speed prediction method using shared weight long short-term memory network and Gaussian process regression,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Wind speed prediction method using shared weight long short-term memory network and Gaussian process regression,

Reference 32

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Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Wind power forecasts using Gaussian processes and numerical weather prediction,

Reference 33

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This paper cites An integrated Gaussian process modeling framework for residential load prediction,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works An integrated Gaussian process modeling framework for residential load prediction,

Reference 34

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This paper cites A sparse heteroscedastic model for the probabilistic load forecasting in energy-intensive enterprises,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works A sparse heteroscedastic model for the probabilistic load forecasting in energy-intensive enterprises,

Reference 35

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This paper cites Probabilistic forecasting of electricity consumption, photovoltaic power generation and net demand of an individual building using Gaussian processes,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Probabilistic forecasting of electricity consumption, photovoltaic power generation and net demand of an individual building using Gaussian processes,

Reference 36

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Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Sparse variational Gaussian process based day-ahead probabilistic wind power forecasting,

Reference 37

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Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Probabilistic net load forecasting based on sparse variational Gaussian process regression,

Reference 38

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This paper cites Multiple output sparse Gaussian processes for short-term electric load forecasting,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Multiple output sparse Gaussian processes for short-term electric load forecasting,

Reference 39

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This paper cites A novel hybrid approach based on variational heteroscedastic Gaussian process regression for multi- step ahead wind speed forecasting,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works A novel hybrid approach based on variational heteroscedastic Gaussian process regression for multi- step ahead wind speed forecasting,

Reference 40

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Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Sparse Gaussian process regression for multi-step ahead forecasting of wind gusts combining numerical weather predictions and on-site measurements,

Reference 41

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This paper cites A Gaussian process regression based hybrid approach for short-term wind speed prediction,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works A Gaussian process regression based hybrid approach for short-term wind speed prediction,

Reference 42

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Gaussian Processes in Power Systems: Techniques, Applications, and Future Works A compositional kernel based Gaussian process approach to day-ahead residential load forecasting,

Reference 43

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Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Evaluating the potential of Gaussian process regression for solar radiation forecasting: A case study,

Reference 44

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Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Robust deep Gaussian process-based probabilistic electrical load fore- casting against anomalous events,

Reference 45

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Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Residential load forecasting: An online-offline deep kernel learning method,

Reference 46

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This paper cites Multi-energy load fore- casting for small-sample integrated energy systems based on neural network Gaussian process and multi-task learning,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Multi-energy load fore- casting for small-sample integrated energy systems based on neural network Gaussian process and multi-task learning,

Reference 47

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Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Probabilistic modelling of wind turbine power curves with application of heteroscedastic Gaussian process regres- sion,

Reference 48

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Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Probabilistic and deterministic wind speed forecasting based on non-parametric approaches and wind characteristics information,

Reference 49

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Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Multitask Bayesian spatiotemporal Gaussian processes for short- term load forecasting,

Reference 50

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This paper cites Probabilistic wind power forecasting for newly-built wind farms based on multi- task Gaussian process method,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Probabilistic wind power forecasting for newly-built wind farms based on multi- task Gaussian process method,

Reference 51

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Observation c82437f5-d34e-46b3-b417-d52da6379e7c · outbound

This paper cites Gaussian process regression for numerical wind speed prediction enhancement,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Gaussian process regression for numerical wind speed prediction enhancement,

Reference 52

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Observation 16fc29ba-02c5-4dd7-b476-74bc6fc4ec2f · outbound

This paper cites Kernel structure design for data-driven probabilistic load flow studies,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Kernel structure design for data-driven probabilistic load flow studies,

Reference 53

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This paper cites A framework for analytical power flow solution using Gaussian process learning,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works A framework for analytical power flow solution using Gaussian process learning,

Reference 54

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This paper cites A data-driven nonparametric approach for probabilistic load-margin assessment considering wind power penetration,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works A data-driven nonparametric approach for probabilistic load-margin assessment considering wind power penetration,

Reference 56

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Observation 4ed27253-4ec6-49d5-a723-b22f3f3a6f95 · outbound

This paper cites Optimal steady-state voltage control using Gaussian process learning,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Optimal steady-state voltage control using Gaussian process learning,

Reference 57

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This paper cites Structure learning in power distribution networks,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Structure learning in power distribution networks,

Reference 58

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This paper cites Data-Efficient Strategies for Probabilistic Voltage Envelopes under Network Contingencies.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Data-Efficient Strategies for Probabilistic Voltage Envelopes under Network Contingencies

Reference 59

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Observation 3be4a5b0-4c05-4bd7-967d-96207e81cbec · outbound

This paper cites Contraction analysis of nonlinear DAE systems,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Contraction analysis of nonlinear DAE systems,

Reference 60

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Observation fff50149-23a7-4453-b637-0ddb8e077a7c · outbound

This paper cites Probabilistic robust small-signal stability framework using Gaussian process learning,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Probabilistic robust small-signal stability framework using Gaussian process learning,

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T15:12:02.430492Z

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Observation 00e2d9be-3adf-4508-86b4-75094ccc7e69 · outbound

This paper cites Physics-informed sparse Gaussian process for probabilistic stability analysis of large-scale power system with dynamic PVs and loads,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Physics-informed sparse Gaussian process for probabilistic stability analysis of large-scale power system with dynamic PVs and loads,

Reference 62

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Observation 312df515-5e0d-424a-a616-9e56d29a252b · outbound

This paper cites A high computationally efficient parallel partial Gaussian process for large-scale power system proba- bilistic transient stability assessment,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works A high computationally efficient parallel partial Gaussian process for large-scale power system proba- bilistic transient stability assessment,

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T15:12:02.440343Z

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Observation bcf818a4-3b7b-4797-b67b-ec8198aa77c8 · outbound

This paper cites Gaussian process learning-based proba- bilistic optimal power flow,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Gaussian process learning-based proba- bilistic optimal power flow,

Reference 64

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Observation 7479d185-3a51-4914-b34d-100c63105c98 · outbound

This paper cites Review on risk assessment of power system,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Review on risk assessment of power system,

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T15:12:02.451937Z

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Observation ff9d3bf1-f0f9-4e6a-9832-fd5d9f7a34be · outbound

This paper cites Scalable risk assessment of rare events in power systems with uncertain wind generation and loads,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Scalable risk assessment of rare events in power systems with uncertain wind generation and loads,

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T15:12:02.458038Z

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Observation feef72aa-544d-4162-97bf-f9ee74bf761f · outbound

This paper cites Power system overloading risk assessment considering topology and renewable uncertainties,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Power system overloading risk assessment considering topology and renewable uncertainties,

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T15:12:02.464552Z

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Observation 74d014c8-e3d8-43a4-b97c-c386ff285e61 · outbound

This paper cites Non-parametric probabilistic load flow using Gaussian process learning,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Non-parametric probabilistic load flow using Gaussian process learning,

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-07T15:12:02.469876Z

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Observation 54a3f607-ef10-47c2-82ac-b037302e5ea8 · outbound

This paper cites A framework for analytical power flow solution using Gaussian process learning,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works A framework for analytical power flow solution using Gaussian process learning,

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T15:12:02.474694Z

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Observation a22f97ce-cadb-4d03-a340-6e7e346e99c1 · outbound

This paper cites Proba- bilistic load-margin assessment using vine copula and Gaussian process emulation,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Proba- bilistic load-margin assessment using vine copula and Gaussian process emulation,

Reference 70

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Observation 769373ca-bbd1-4b58-b236-b245c0f18b6b · outbound

This paper cites Probabilistic power flow based on a Gaussian process emulator,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Probabilistic power flow based on a Gaussian process emulator,

Reference 71

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Observation dddb2e48-b260-45d7-b912-5a119a7d422f · outbound

This paper cites Online Gaussian process learning for security assessment,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Online Gaussian process learning for security assessment,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.265426Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d02bd448-caea-4f65-89fb-8e33f13edccd · outbound

This paper cites Probabilistic stability analysis: the way forward for stability analysis of sustainable power systems,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Probabilistic stability analysis: the way forward for stability analysis of sustainable power systems,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.247076Z

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Observation d785a735-d858-4b0f-8193-97ae6fa9650a · outbound

This paper cites Transferable deep kernel emulator for probabilistic load margin assessment with topology changes, uncertain renewable generations and loads,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Transferable deep kernel emulator for probabilistic load margin assessment with topology changes, uncertain renewable generations and loads,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.231067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 580a5b2d-8740-4ab4-8b4d-527dfd39283b · outbound

This paper cites Dynamic security assessment of small-signal stability for power grids using windowed online Gaussian process,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Dynamic security assessment of small-signal stability for power grids using windowed online Gaussian process,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.214568Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ee6a6884-8f0f-4c2e-81e1-276bca36a9a4 · outbound

This paper cites Inferring power system frequency oscillations using Gaussian processes,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Inferring power system frequency oscillations using Gaussian processes,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.181544Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation faeb5c63-f07f-4215-a3b6-d40488f8bd31 · outbound

This paper cites Interpretable data-driven probabilistic power system load margin assessment with uncertain renewable energy and loads,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Interpretable data-driven probabilistic power system load margin assessment with uncertain renewable energy and loads,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.166765Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e9e2b093-2eb5-4b4b-9f88-66e15d0a7666 · outbound

This paper cites Gaussian process regression based inertia emulation and reserve estimation for grid interfaced photovoltaic system,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Gaussian process regression based inertia emulation and reserve estimation for grid interfaced photovoltaic system,

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.148461Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3c29f217-31f1-4bd2-ae3a-75b0ca411e91 · outbound

This paper cites Estimating the region of attraction for power systems using Gaussian process and converse lyapunov function,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Estimating the region of attraction for power systems using Gaussian process and converse lyapunov function,

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.132478Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 195f0012-91c1-413e-b953-46e7132bae20 · outbound

This paper cites Bayesian post-fault power system dynamic trajectory prediction,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Bayesian post-fault power system dynamic trajectory prediction,

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.116979Z

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Observation 9be9611b-c368-4023-b52e-ef1f7b8df1fd · outbound

This paper cites Improvement of Gaussian process predictor of electric power damage caused by typhoons considering time-varying characteristics,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Improvement of Gaussian process predictor of electric power damage caused by typhoons considering time-varying characteristics,

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.100251Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1380bc8b-657b-4f8f-9e27-b9f266afba11 · outbound

This paper cites Data driven approach for fault detection and Gaussian process regression based location prognosis in smart ac microgrid,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Data driven approach for fault detection and Gaussian process regression based location prognosis in smart ac microgrid,

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.082976Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7231633f-7421-4d32-a1b4-2f6577ce9a63 · outbound

This paper cites A robust fault detection and location prediction module using support vector machine and Gaussian process regression for AC microgrid,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works A robust fault detection and location prediction module using support vector machine and Gaussian process regression for AC microgrid,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.065056Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7f77c0fc-71f9-4c37-b6e4-6a1fa68b7b32 · outbound

This paper cites Wind turbine fault diagnosis based on Gaussian process classifiers applied to operational data,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Wind turbine fault diagnosis based on Gaussian process classifiers applied to operational data,

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.049012Z

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Observation f21d98d2-0dd3-47c8-afab-86c04ad026b8 · outbound

This paper cites The prediction method on the early failure of hydropower units based on Gaussian process regression driven by monitoring data,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works The prediction method on the early failure of hydropower units based on Gaussian process regression driven by monitoring data,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.031574Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4396f73a-d31d-4b78-a3dd-769332ee2769 · outbound

This paper cites A data-driven mixed integer programming approach for joint chance-constrained optimal power flow under uncertainty,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works A data-driven mixed integer programming approach for joint chance-constrained optimal power flow under uncertainty,

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.014248Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5b064e40-2609-4a77-a03d-db3e0b18d6fb · outbound

This paper cites Data-driven stochastic AC-OPF using Gaussian process regression,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Data-driven stochastic AC-OPF using Gaussian process regression,

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:03.996315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1ef425d6-921d-42b0-aae6-e1e5d77d2391 · outbound

This paper cites Fast data-driven chance constrained AC-OPF using hybrid sparse Gaussian processes,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Fast data-driven chance constrained AC-OPF using hybrid sparse Gaussian processes,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:03.978501Z

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Observation d06106c0-07bb-4863-a7bb-3d485dc3e3fa · outbound

This paper cites Supervised learning for optimal power flow as a real-time proxy,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Supervised learning for optimal power flow as a real-time proxy,

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:03.960596Z

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Observation 54904b11-c45f-46b3-91e3-fdde4472982a · outbound

This paper cites Analytical uncertainty propagation for multi-period stochastic optimal power flow,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Analytical uncertainty propagation for multi-period stochastic optimal power flow,

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:03.942870Z

Source-reported events for the cited work

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Observation 8da22388-6817-4dd9-964d-ac2a8345e0a8 · outbound

This paper cites Analytic neural network Gaussian process enabled chance-constrained voltage regulation for active distribution systems with PVs, batteries and EVs,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Analytic neural network Gaussian process enabled chance-constrained voltage regulation for active distribution systems with PVs, batteries and EVs,

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:03.924526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ce6edc6f-d6c4-49ff-8c19-4f94f2e41ecd · outbound

This paper cites Fast inverter control by learning the opf mapping using sensitivity- informed Gaussian processes,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Fast inverter control by learning the opf mapping using sensitivity- informed Gaussian processes,

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:03.907219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a290a1b7-68a8-458e-a1a3-ba477afdf141 · outbound

This paper cites Gaussian process regression-based smart inverters’ V olt-V AR control,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Gaussian process regression-based smart inverters’ V olt-V AR control,

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:03.890745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation edfecd3c-1b27-4ec3-83c8-10302e26f0f5 · outbound

This paper cites Data- driven energy management system with Gaussian process forecasting and MPC for interconnected microgrids,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Data- driven energy management system with Gaussian process forecasting and MPC for interconnected microgrids,

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:03.873855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 21f392fd-8c08-4eea-ba15-efd7de05c080 · outbound

This paper cites Optimal operation of an energy management system using model predictive control and Gaussian process time-series modeling,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Optimal operation of an energy management system using model predictive control and Gaussian process time-series modeling,

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:03.856320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 804e99a9-af9c-4769-9670-e628c3496fdf · outbound

This paper cites Data-driven demand response modeling and control of buildings with Gaussian processes,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Data-driven demand response modeling and control of buildings with Gaussian processes,

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:03.839677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 68d2a623-4d8e-481c-9b54-1904aeb56b3e · outbound

This paper cites Deep sigma point processes-assisted chance-constrained power system transient stability preventive control,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Deep sigma point processes-assisted chance-constrained power system transient stability preventive control,

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:03.824228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d33e38d4-cb14-4ed1-8300-734550188943 · outbound

This paper cites Safe reinforcement learning-based transient stability control for islanded microgrids with topology reconfiguration,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Safe reinforcement learning-based transient stability control for islanded microgrids with topology reconfiguration,

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:03.808473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a0ea3bc0-e951-4581-a601-355e0e93825f · outbound

This paper cites Gaussian process-based bayesian opti- mization for data-driven unit commitment,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Gaussian process-based bayesian opti- mization for data-driven unit commitment,

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:03.791585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation acf3b71f-0420-4607-892d-c2e3ead6aa4f · outbound

This paper cites an unresolved cited work.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Unresolved cited work

Reference 101

Resolution: unresolved; no resolver link, observed 2026-08-07T15:12:02.637703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f40cd214-7d4a-4295-8767-8e947b1ad07d · outbound

This paper cites Degradation-infused energy portfolio allocation framework: Risk-averse fair storage participation,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Degradation-infused energy portfolio allocation framework: Risk-averse fair storage participation,

Reference 102

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:03.765646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2f4ea617-c37a-4125-9781-94873c847f93 · outbound

This paper cites Inferring power system dynamics from synchrophasor data using Gaussian processes,.

Gaussian Processes in Power Systems: Techniques, Applications, and Future Works Inferring power system dynamics from synchrophasor data using Gaussian processes,

Reference 103

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:04.197744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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