Time Series Representation

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Table of contents

1 introduction 
1.1 Context and goals of this work
1.2 Methods
1.3 Organisation
2 related work 
3 time series’s generation and forecasting from disentangled representations of contexts 
3.1 Related work
3.2 Model
3.3 Experiments
3.4 Conclusion
4 driver and context recognition from can data using disentangled representations
4.1 Driving Behaviour Assessment
4.2 Our Data Driven Approach Based on CAN Data
4.3 Conclusion
5 conclusion 
5.1 Where we began
5.2 Where we are now
5.3 Perspectives