Comments (2)
The latter is correct.
Use case: Ulrich wants me to predict electrical exitation from a displacement field.
So (δx, δy, δz) → u
The displacement field is a vector field and could be interpreted as multiple scalar fields.
from timeseriesprediction.jl.
is this just a convenience for not calling reconstruct
and timeseriesprediction
multiple times, or is there anything actually new here?
Do you suggest to be able to use multiple spatiotemporal fields to predict some other single field?
from timeseriesprediction.jl.
Related Issues (20)
- Move documentation of TSPred to this repo.
- Issue with light cone embedding
- Implement a CompositeBoundary HOT 1
- Prediction of flow dynamics using point processes (new prediction scheme)
- Documentation of SymmetricSpatialEmbedding
- ArgumentError: principal variance cannot exceed total variance. HOT 9
- Documentation: light_cone_embedding and r0 HOT 2
- Nearest Trajectory Strategy for Time Series Prediction HOT 2
- Barkley in tests/system_defs.jl is very slow
- Consistency of source code for crossprediction
- versions, documentation, paper
- Use multiple input timeseries as training HOT 1
- Remove duplication of inner to reduce source
- Better Boundary Conditions
- LoadError: UndefVarError: AbstractEmbedding not defined HOT 4
- Is this repo supported? HOT 2
- error to run timeseriesprediction.ipynb HOT 1
- Compile fail : AbstractDataset not defined HOT 2
- TagBot trigger issue HOT 10
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from timeseriesprediction.jl.