Search Results for author:
Found 3 papers, 1 papers with code
Cross Domain Image Generation through Latent Space Exploration with Adversarial Loss
Conditional domain generation is a good way to interactively control sample generation process of deep generative models.
The Level Weighted Structural Similarity Loss: A Step Away from the MSE
The Mean Square Error (MSE) has shown its strength when applied in deep generative models such as Auto-Encoders to model reconstruction loss.
Not All Features Are Equal: Feature Leveling Deep Neural Networks for Better Interpretation
Self-explaining models are models that reveal decision making parameters in an interpretable manner so that the model reasoning process can be directly understood by human beings.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
