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I am just wondering if you forgot to set 'use_deterministic_path'= True for ANP-RNN, since in the paper the authors indicate so, and you obviously have already set cross-validations.
BTW, I was trying to replicate the experiment on GP dataset, and I have already implemented an ANP. Although the architecture of mine is slightly different from yours, I assume I will just need to replace all the MLPs with LSTMs plus sequential encodings of the input, output, right? However, mine result was really bad, when I sorted my x_context, x_target, the model only seems to be able to predict a few points and predicts flat curves afterwards. Could you please share with me any hints regarding this?
Your help is very much appreciated
The text was updated successfully, but these errors were encountered:
Hi there,
I am just wondering if you forgot to set 'use_deterministic_path'= True for ANP-RNN, since in the paper the authors indicate so, and you obviously have already set cross-validations.
https://github.com/3springs/attentive-neural-processes/blob/af431a267bad309b2d5698f25551986e2c4e7815/neural_processes/models/neural_process/lightning.py#L189-L195
BTW, I was trying to replicate the experiment on GP dataset, and I have already implemented an ANP. Although the architecture of mine is slightly different from yours, I assume I will just need to replace all the MLPs with LSTMs plus sequential encodings of the input, output, right? However, mine result was really bad, when I sorted my x_context, x_target, the model only seems to be able to predict a few points and predicts flat curves afterwards. Could you please share with me any hints regarding this?
Your help is very much appreciated
The text was updated successfully, but these errors were encountered: