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You should try an architecture with an encoder and a decoder. The encoder will consume all the data you give as in put and decoder will give out the series of output.


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An interesting model I encountered in a course is Facebook Prophet. Prophet takes into account trends, seasonality, and holidays for its predictions. As you can probably guess, this is a model that fits Facebook's needs very well. I'll give a brief introduction then provide a link where you can read more. Prophet fits a couple of functions of time ...


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That does not seem very useful to apply local minima search (as SGD) to another local minima search. Existing successful solutions combine global minima search techniques with local minima search. For example, it's beneficial to combine simulated annealing with SGD to optimize it's learning rate and/or Nesterov momentum. In this case, you don't even need to ...


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Single object tracking using a Siamese Network is a Detect and compare approach, where an object of interest is detected and the one to be tracked is passed through a siam network with next consecutive frame to get a correlation between them, if you look at the related reference, it is a correlation-based tracking, ie. correlation between objects detected in ...


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