Chong Mou

Thanks for your reply! Does it mean the l_forw_ce = self.train_opt['lambda_ce_forw'] * torch.sum(z**2) / z.shape[0] is only an assistant component rather than a strict constraint of gaussian distributions?

Thanks for your reply! Does it mean the l_forw_ce = self.train_opt['lambda_ce_forw'] * torch.sum(z**2) / z.shape[0] is only an assistant component rather than a strict constraint of gaussian distributions?

Thanks for your reply! Does it mean the l_forw_ce = self.train_opt['lambda_ce_forw'] * torch.sum(z**2) / z.shape[0] is only an assistant component rather than a strict constraint of gaussian distributions?

I konw you want to use "pad" to keep the same length , but "pad" is not part of the ground truth , you need to remove them when you...

Thanks for your attention. We are working on it.

Sorry for the late reply. A is learnable, capturing the degradation matrix through training data, as in [1] and [2]. [1] Deep Memory-Augmented Proximal Unrolling Network for Compressive Sensing [2]...

Thanks for your attention. This is a version issue of numpy. Please update numpy.

Sorry for the late reply. What's the result of your training?