Open hojjatkarami opened 9 months ago
Sorry, I did not save the code for the baselines. You can adapt them in their corresponding repos. The idea is just following how we use RTSGAN to generate incomplete time series: Treat each missing value as an additional mask to generate and use the synthetic masks to form the final irregularly sampled time series.
Hi,
Could you share the hyperparameters for replicating RTSGAN results on stock and energy datasets?
Thanks
You can check the parameter setting in the paper: For stock, it is default in the code and for Energy, it should be --hidden-dim 112 --embed-dim 448 --noise-dim 448 --layers 3
Hello,
could you please kindly share with me how did you adapt TimeGAN and DoppelGANger to irregularly sampled time series dataset?
I would appreciate it if you have any code with me. Or any additional library if you used.
Many thanks