hello，I completely agree with your idea about Neural CDE. Maybe I'm a bit clumsy, I've seen your discussions with others before. But I still don't quite understand, sorry. We all know that this model can predict on time series without dividing the training and testing sets? Just need to interpolate and predict on a time series. But I have about 100 samples in your example of predicting helical chirality. I don't quite understand this point. In addition, what is the interpolation and prediction process when the sample has multiple time series features? thank you
hello，I completely agree with your idea about Neural CDE. Maybe I'm a bit clumsy, I've seen your discussions with others before. But I still don't quite understand, sorry. We all know that this model can predict on time series without dividing the training and testing sets? Just need to interpolate and predict on a time series. But I have about 100 samples in your example of predicting helical chirality. I don't quite understand this point. In addition, what is the interpolation and prediction process when the sample has multiple time series features? thank you