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Anomaly detection for images

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I couldn't get as much accuracy as the results in the paper, is there something wrong with the code? For example, are the hyperparameters different, or is the architecture different...

it seems that it doesn't work well and have a few bugs? such as the checkpoint_dir and the loss_function is not appropriate.

Can you tell me how to use this function in EBM? x_t = x_t - eps * x_grad * (x_t - recon_x) ** 2 eps is not defined in train.py