Hello, I was impressed with your paper.
I want to experiment with your paper for forecasting stock data.
so, I have some questions.
-
is the 'wnet_simple.py' implementation of your paper concept in Lorenz data?
So, what's in the readme is the difference between your article and waveNet?
-
in Figure 2.3, Is input and Condition data passed through dilated convolution (and parametrized skip connection) simply added?
-
I configured the data [batch size, 1, 10, channels = number of the another data(features)], so I ran by channels(Of course, skip connection was also configured for each channel). Is that what I understand correctly?
I would appreciate your reply.
Hello, I was impressed with your paper.
I want to experiment with your paper for forecasting stock data.
so, I have some questions.
is the 'wnet_simple.py' implementation of your paper concept in Lorenz data?
So, what's in the readme is the difference between your article and waveNet?
in Figure 2.3, Is input and Condition data passed through dilated convolution (and parametrized skip connection) simply added?
I configured the data [batch size, 1, 10, channels = number of the another data(features)], so I ran by channels(Of course, skip connection was also configured for each channel). Is that what I understand correctly?
I would appreciate your reply.