A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings | Paper Citation Record

Observation 1464a6d5-9367-4f90-92e1-3f83ff7619c4 · outbound

This paper cites Deterministic nonperiodic ﬂow,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Deterministic nonperiodic ﬂow,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.608189Z

Source-reported events for the cited work

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

Observation 6ef3403e-3e9d-4dce-90e7-41e4cf5d158b · outbound

This paper cites ˆU ∈ Rnq×r, ˆS ∈ Rr×r and ˆV∈ R(N−q)×r, and [X F]T = ˜U˜S˜V∗ with the truncation value selected as p, so that ˜U∈ R(n+n′)q×p, ˜S∈ Rp×p and ˜V∈ R(N−q)×p.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings ˆU ∈ Rnq×r, ˆS ∈ Rr×r and ˆV∈ R(N−q)×r, and [X F]T = ˜U˜S˜V∗ with the truncation value selected as p, so that ˜U∈ R(n+n′)q×p, ˜S∈ Rp×p and ˜V∈ R(N−q)×p

Reference 2

Resolution: malformed identifier; raw_fallback, observed 2026-08-14T10:07:35.624028Z

Source-reported events for the cited work

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

Observation 73daed3d-f81b-465e-bbd2-382ba21683e1 · outbound

This paper cites an unresolved cited work.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-14T10:07:35.593134Z

Source-reported events for the cited work

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

Observation 45543326-3893-4c31-8b33-23e079894a85 · outbound

This paper cites Long-term research challenges in wind energy - A research agenda by the European academy of wind energy,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Long-term research challenges in wind energy - A research agenda by the European academy of wind energy,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.577670Z

Source-reported events for the cited work

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

Observation af4cee4d-38ff-4f40-bdba-a59f42ceebdf · outbound

This paper cites Duriez, S.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Duriez, S

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.562464Z

Source-reported events for the cited work

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

Observation e402e289-edd5-45a9-bbfe-17a2bb47e5a3 · outbound

This paper cites Challenges in climate science and contemporary applied mathematics,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Challenges in climate science and contemporary applied mathematics,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.547335Z

Source-reported events for the cited work

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

Observation dbaa2b51-63aa-4e80-97e8-70796f0c0a60 · outbound

This paper cites The quiet revolution of numerical weather prediction,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings The quiet revolution of numerical weather prediction,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.532819Z

Source-reported events for the cited work

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

Observation 8f222c87-1188-46cd-92a1-de114696892a · outbound

This paper cites Model error, information barriers, state estimation and prediction in complex multiscale systems,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Model error, information barriers, state estimation and prediction in complex multiscale systems,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.517839Z

Source-reported events for the cited work

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

Observation 17409448-ed8d-4361-bb7f-63eef77b25b4 · outbound

This paper cites A variational approach to probing extreme events in turbu- lent dynamical systems,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings A variational approach to probing extreme events in turbu- lent dynamical systems,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.503071Z

Source-reported events for the cited work

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

Observation 3fa13e5d-6cf3-4311-8741-8bb17974b0c0 · outbound

This paper cites The interpretation of short climate records, with comments on the North Atlantic and Southern Oscillations,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings The interpretation of short climate records, with comments on the North Atlantic and Southern Oscillations,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.488151Z

Source-reported events for the cited work

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

Observation f4865fdb-565e-4333-b890-88341df96b44 · outbound

This paper cites Van den Dool, Empirical methods in short-term climate prediction (Oxford University Press, 2007).

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Van den Dool, Empirical methods in short-term climate prediction (Oxford University Press, 2007)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.472068Z

Source-reported events for the cited work

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

Observation de698f90-7fdb-4413-a05e-2ce6a3c37e58 · outbound

This paper cites The skill of atmospheric linear inverse models in hindcasting the Madden–Julian Oscillation,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings The skill of atmospheric linear inverse models in hindcasting the Madden–Julian Oscillation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.456165Z

Source-reported events for the cited work

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

Observation be76a75e-88ae-4f8f-8808-bcb69fc36738 · outbound

This paper cites Data-driven spectral decomposition and forecasting of ergodic dynamical sys- tems,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Data-driven spectral decomposition and forecasting of ergodic dynamical sys- tems,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.441225Z

Source-reported events for the cited work

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

Observation efab9e51-4136-4aea-82fd-4af6e0d7bd76 · outbound

This paper cites Data-driven prediction strategies for low-frequency patterns of North Paciﬁc climate variability,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Data-driven prediction strategies for low-frequency patterns of North Paciﬁc climate variability,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.425355Z

Source-reported events for the cited work

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

Observation 047f3fca-b1d1-408c-922b-c5d0dda300e3 · outbound

This paper cites Data-driven reduced modelling of turbulent Rayleigh- B´ enard convection using dmd-enhanced ﬂuctuation-dissipation theorem,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Data-driven reduced modelling of turbulent Rayleigh- B´ enard convection using dmd-enhanced ﬂuctuation-dissipation theorem,

Reference 15

Resolution: verified exact; doi, observed 2026-08-14T10:07:34.734631Z

Source-reported events for the cited work

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

Observation 37e78af1-3d2b-4d41-b575-e1c18a1bf725 · outbound

This paper cites An ensemble quadratic echo state network for non-linear spatio-temporal forecasting,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings An ensemble quadratic echo state network for non-linear spatio-temporal forecasting,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.408746Z

Source-reported events for the cited work

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

Observation e36a1d65-2989-4d91-abbf-82c9001083af · outbound

This paper cites Long-term Forecasting using Higher Order Tensor RNNs.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Long-term Forecasting using Higher Order Tensor RNNs

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-14T10:07:34.503637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50a4ce34-6860-4641-b6cb-dc05f64080d2 · outbound

This paper cites Data-driven fore- casting of high-dimensional chaotic systems with long short-term memory networks,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Data-driven fore- casting of high-dimensional chaotic systems with long short-term memory networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.392395Z

Source-reported events for the cited work

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

Observation 46a29765-79bc-41ac-8553-c2319ba33ecb · outbound

This paper cites Model-free prediction of large spatiotem- porally chaotic systems from data: A reservoir computing approach,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Model-free prediction of large spatiotem- porally chaotic systems from data: A reservoir computing approach,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.377102Z

Source-reported events for the cited work

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

Observation 1c5c9fa6-0726-4dec-82d5-d4ed5fa018bc · outbound

This paper cites Physics-informed neural networks: A deep learning framework for learning forward and inverse problems involving nonlinear partial diﬀerential equations,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Physics-informed neural networks: A deep learning framework for learning forward and inverse problems involving nonlinear partial diﬀerential equations,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.361392Z

Source-reported events for the cited work

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

Observation faa6b0c4-2b88-4a4d-9922-791e2ddfd389 · outbound

This paper cites Compressed Convolutional LSTM: An Efficient Deep Learning framework to Model High Fidelity 3D Turbulence.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Compressed Convolutional LSTM: An Efficient Deep Learning framework to Model High Fidelity 3D Turbulence

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-14T10:07:34.522251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 118e00e6-163b-4371-96c4-5c04fd71075f · outbound

This paper cites Deep state networks with uncertainty quantiﬁcation for spatio-temporal forecasting,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Deep state networks with uncertainty quantiﬁcation for spatio-temporal forecasting,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.346094Z

Source-reported events for the cited work

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

Observation a2d4b553-d67b-4683-a39d-4cbe92cbe797 · outbound

This paper cites Data-driven prediction of a multi-scale Lorenz 96 chaotic system using deep learning methods: Reservoir computing, ANN, and RNN-LSTM.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Data-driven prediction of a multi-scale Lorenz 96 chaotic system using deep learning methods: Reservoir computing, ANN, and RNN-LSTM

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-14T10:07:34.531821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fa49968-40dd-435e-a11d-b75a33d15030 · outbound

This paper cites Hamiltonian systems and transformation in Hilbert space,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Hamiltonian systems and transformation in Hilbert space,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.330331Z

Source-reported events for the cited work

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

Observation a7d988db-e6a7-42cd-8b3b-a4cbba7a0ee5 · outbound

This paper cites Spectral properties of dynamical systems, model reduction and decompositions,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Spectral properties of dynamical systems, model reduction and decompositions,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.314874Z

Source-reported events for the cited work

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

Observation 2b7b8170-b2b0-40a4-b4e1-03985f7197ac · outbound

This paper cites Analysis of ﬂuid ﬂows via spectral properties of the Koopman operator,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Analysis of ﬂuid ﬂows via spectral properties of the Koopman operator,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.299067Z

Source-reported events for the cited work

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

Observation 642faa99-16de-495f-ba2d-d13e2aeae254 · outbound

This paper cites Dynamic mode decomposition of numerical and experimental data,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Dynamic mode decomposition of numerical and experimental data,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.282903Z

Source-reported events for the cited work

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

Observation 9496c846-5945-4678-99fe-6fa695f0b71d · outbound

This paper cites Spectral analysis of nonlinear ﬂows,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Spectral analysis of nonlinear ﬂows,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.266822Z

Source-reported events for the cited work

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

Observation b1b05904-327c-4fda-8f0a-903e36daa6ba · outbound

This paper cites On dynamic mode decomposition: Theory and applications,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings On dynamic mode decomposition: Theory and applications,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.251551Z

Source-reported events for the cited work

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

Observation 56e437a4-2cef-4a5b-9df1-c09738811fa4 · outbound

This paper cites A data–driven approximation of the Koopman operator: Extending dynamic mode decomposition,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings A data–driven approximation of the Koopman operator: Extending dynamic mode decomposition,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.235731Z

Source-reported events for the cited work

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

Observation 3bc46067-19ec-425c-8ec3-d50a7f40a36a · outbound

This paper cites Ergodic theory, dynamic mode decomposition, and computation of spectral properties of the Koopman operator,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Ergodic theory, dynamic mode decomposition, and computation of spectral properties of the Koopman operator,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.218890Z

Source-reported events for the cited work

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

Observation eaf0a33a-278e-40a9-a64a-5273aa2e9cf3 · outbound

This paper cites Study of dynamics in post-transient ﬂows using Koopman mode decomposition,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Study of dynamics in post-transient ﬂows using Koopman mode decomposition,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.203005Z

Source-reported events for the cited work

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

Observation f6d0da0a-113d-4848-8d60-f6156247cbb1 · outbound

This paper cites On convergence of extended dynamic mode decomposition to the Koopman operator,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings On convergence of extended dynamic mode decomposition to the Koopman operator,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.187758Z

Source-reported events for the cited work

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

Observation 302bce05-1bbf-49be-bdc2-32956f356774 · outbound

This paper cites Model reduction for ﬂow analysis and control,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Model reduction for ﬂow analysis and control,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.171820Z

Source-reported events for the cited work

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

Observation 93cd01d4-c435-4f00-b6bc-a1d6ddd79b9b · outbound

This paper cites Detecting strange attractors in turbulence,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Detecting strange attractors in turbulence,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.156298Z

Source-reported events for the cited work

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

Observation 7c5acbb1-34d7-48a0-9e60-4c54d2f457ee · outbound

This paper cites Linear predictors for nonlinear dynamical systems: Koopman oper- ator meets model predictive control,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Linear predictors for nonlinear dynamical systems: Koopman oper- ator meets model predictive control,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.140034Z

Source-reported events for the cited work

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

Observation 06e5b2b4-74aa-42e5-9c67-0e6d490e64b5 · outbound

This paper cites A data-driven Koopman model predictive control framework for nonlinear flows.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings A data-driven Koopman model predictive control framework for nonlinear flows

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-14T10:07:34.598352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dada5588-3ec0-45e2-b109-6385cbbf5fb2 · outbound

This paper cites Nonlinear laplacian spectral analysis for time series with intermittency and low-frequency variability,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Nonlinear laplacian spectral analysis for time series with intermittency and low-frequency variability,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.125160Z

Source-reported events for the cited work

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

Observation 11348528-818a-41a6-8116-856efa31bcec · outbound

This paper cites Chaos as an intermittently forced linear system,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Chaos as an intermittently forced linear system,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.110721Z

Source-reported events for the cited work

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

Observation 1970b96a-351f-474c-a2c5-0805dee18080 · outbound

This paper cites Discovering governing equations from data by sparse identiﬁcation of nonlinear dynamical systems,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Discovering governing equations from data by sparse identiﬁcation of nonlinear dynamical systems,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.095136Z

Source-reported events for the cited work

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

Observation 9f72c4b6-7785-4927-a3ed-593c8c1d0adc · outbound

This paper cites Matrix pencils in time and frequency domain system identiﬁcation,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Matrix pencils in time and frequency domain system identiﬁcation,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.079844Z

Source-reported events for the cited work

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

Observation 4605c522-75b9-45f8-a5c9-7530e1fb9ec6 · outbound

This paper cites Model reduction of bilinear systems in the Loewner framework,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Model reduction of bilinear systems in the Loewner framework,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.064966Z

Source-reported events for the cited work

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

Observation b8de00cf-c9c9-4aeb-8509-57ea054d97f8 · outbound

This paper cites On the Loewner framework for model reduction of Burgers’ equation,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings On the Loewner framework for model reduction of Burgers’ equation,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.050012Z

Source-reported events for the cited work

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

Observation c14729d0-589c-4194-a336-32dc74743e37 · outbound

This paper cites Gugercin, C.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Gugercin, C

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.034720Z

Source-reported events for the cited work

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

Observation 815335be-2c43-4fda-9b83-f6151e10578e · outbound

This paper cites Clustering of Series via Dynamic Mode Decomposition and the Matrix Pencil Method.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Clustering of Series via Dynamic Mode Decomposition and the Matrix Pencil Method

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:07:34.757258Z

Source-reported events for the cited work

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

Observation 07f55ee1-9775-4dd0-a87c-955b5091d71f · outbound

This paper cites Dynamic mode decomposition with control,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Dynamic mode decomposition with control,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.019039Z

Source-reported events for the cited work

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

Observation c187e978-d49b-4b21-a725-b8dfe93d145b · outbound

This paper cites Determining Lyapunov exponents from a time series,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Determining Lyapunov exponents from a time series,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:35.003310Z

Source-reported events for the cited work

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

Observation 2a27c3b0-dac2-403c-8f12-143a86124e1b · outbound

This paper cites Statistically accurate low-order models for uncertainty quantiﬁ- cation in turbulent dynamical systems,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Statistically accurate low-order models for uncertainty quantiﬁ- cation in turbulent dynamical systems,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:34.987646Z

Source-reported events for the cited work

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

Observation af49bcaa-5e34-4f11-941b-c468b2cd0e75 · outbound

This paper cites Introduction to turbulent dynamical systems for complex systems,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Introduction to turbulent dynamical systems for complex systems,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:34.971461Z

Source-reported events for the cited work

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

Observation 0a6ad61e-627f-427a-b62c-4ac2062f59c2 · outbound

This paper cites Low-dimensional reduced-order models for statistical response and uncertainty quantiﬁcation: Two-layer baroclinic turbulence,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Low-dimensional reduced-order models for statistical response and uncertainty quantiﬁcation: Two-layer baroclinic turbulence,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:34.954974Z

Source-reported events for the cited work

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

Observation b4aa50c1-0b4e-4bad-9b63-a96d6af4142c · outbound

This paper cites an unresolved cited work.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-14T10:07:34.937347Z

Source-reported events for the cited work

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

Observation 9a06f893-115c-47b1-a945-b2d988ef8192 · outbound

This paper cites Predictability - a problem partly solved,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Predictability - a problem partly solved,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:34.920071Z

Source-reported events for the cited work

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

Observation 5173e43a-43c1-4799-9e99-f17439fb3a88 · outbound

This paper cites High-Re solutions for incompressible ﬂow using the Navier-Stokes equations and a multigrid method,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings High-Re solutions for incompressible ﬂow using the Navier-Stokes equations and a multigrid method,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:34.902781Z

Source-reported events for the cited work

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

Observation 1ae8c3c2-0b11-490d-b959-ccfb277afafd · outbound

This paper cites Driven cavity ﬂows by eﬃcient numerical techniques,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Driven cavity ﬂows by eﬃcient numerical techniques,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:34.884988Z

Source-reported events for the cited work

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

Observation 17f3f084-9cf6-4ee1-a456-8b552462e2c4 · outbound

This paper cites A novel fully implicit ﬁnite volume method applied to the lid- driven cavity problempart I: High Reynolds number fow calculations,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings A novel fully implicit ﬁnite volume method applied to the lid- driven cavity problempart I: High Reynolds number fow calculations,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:34.870118Z

Source-reported events for the cited work

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

Observation 22e9ed92-736e-4f4f-996f-1b9daf2038fa · outbound

This paper cites Linearly recurrent autoencoder networks for learning dynamics,.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Linearly recurrent autoencoder networks for learning dynamics,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:34.855063Z

Source-reported events for the cited work

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

Observation d3c9cc89-c3c1-41e0-9ace-88b94efb7918 · outbound

This paper cites Singular Value Decomposition (svd) and Principal Component Analysis (PCA),.

A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings Singular Value Decomposition (svd) and Principal Component Analysis (PCA),

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:07:34.839687Z

Source-reported events for the cited work

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

Coverage vector

Reference resolution

Outbound references

Pith citing papers