Comments (2)
Hello @vladyskai ,
You can use the LTC or CfC layer as any other tf.keras layer while building the model.
For better understanding of time series forecasting using Neural Networks please follow articles available online. I followed the one which uses LSTM for forecasting.
Replace the LSTM model with LTC or CfC or combination of both the layers and you can run it perfectly fine.
How to add LTC/CfC layers to keras model?
Follow the codes mentioned in the following link
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Hello @vladyskai , You can use the LTC or CfC layer as any other tf.keras layer while building the model. For better understanding of time series forecasting using Neural Networks please follow articles available online. I followed the one which uses LSTM for forecasting. Replace the LSTM model with LTC or CfC or combination of both the layers and you can run it perfectly fine. How to add LTC/CfC layers to keras model? Follow the codes mentioned in the following link
Thank you for your answer!
from ncps.
Related Issues (20)
- Evaluate model HOT 1
- 200GB data :)
- In file: ltc_example_sinusoidal.ipynb: error NameError: name 'wirings' is not defined HOT 1
- Reproducibility issue: low rewards in Atari examples HOT 4
- why [-1, 1, 1]? HOT 2
- TypeError: SequenceLearner.optimizer_step() missing 1 required positional argument: 'closure' HOT 1
- Example of stacking LTC with convolutional layers on pytorch version HOT 2
- Issues on recurrent connections in command layer for CfC
- getting issues while saving model HOT 2
- Input dimension HOT 1
- LtC and CfC implementation questions
- Pytorch model behaves differently after saving HOT 1
- How to define Output Dimension in NCP/LTC network?
- Example for image sequence classifier HOT 3
- Defining equal input and output shapes for LTC HOT 1
- Python gives anRuntime error when I try to send hidden state (hx) to the CfC model. HOT 2
- way to get 200G dataset
- What dependency versions? HOT 4
- module 'tensorflow.keras.layers' has no attribute 'AbstractRNNCell' HOT 2
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