Comments (2)
Would this model be over the top or could it be used for prediction of future values.
Kind regards and thanks,
Andrew
from torchcde.
In the sense of time series forecasting? Sure. You could do a sequence-to-sequence encoder/decoder pair. Neural CDE as the encoder, then probably a Neural ODE as the decoder.
from torchcde.
Related Issues (20)
- setup.py and torchsde HOT 1
- Breaking install HOT 4
- publish `torchcde` on PyPI HOT 1
- Consider opening a GH discussions HOT 13
- Online prediction tasks needs examples HOT 4
- About how to use on seq2seq works HOT 5
- Sequence outputs from Neural ODE (similar to 'many to many' RNN)? HOT 3
- CDEs with Image Data HOT 1
- Comparison to alternative ODE models HOT 4
- About how to use CDE in Variational Autoencoders? HOT 1
- Integration to pytorch lighting pipeline HOT 1
- piping in & predicting arbitrary streams of values
- Very slow training with market data, normal? HOT 1
- much slower when using torchsde as backend. HOT 2
- Integrate the ODE function of the CDE system to infinity HOT 2
- Please consider create conda distribution (maybe conda-forge?) HOT 1
- Prediction of irregular time series HOT 1
- Masking Coefficients? HOT 2
- Seq2seq forecasting: adding temporal information and extrapolation
- Overfitting
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