Meta-Learning for Time Series Forecasting (DeepTime) in PyTorch Lightning
This article is devoted to describing a new type of deep learning model to cope with the usual problems in time series (covariate shift and conditional distribution shift)-come from being non-stationary-by using meta-learning formulation to forecast the future. The model is named DeepTime, which is a deep time-index model combined with using meta-learning. This model is a great example of the model’s synergies with a meta-learning formulation for time series forecasting.
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DeepTime in one Figure
In General, you can see there are three types of layers in DeepTime:
- Ridge Regressor
- Multi-layer Perceptron (MLP)
- Random Fourier Features
Let’s see what these are layer doing:
1. Ridge Regressor
2. MLP (multi-layer perceptron)
Well, nothing new!! These are the linear regression formula that we use in simple (and, of…