4 citations · 5 across the 2 of their papers we have counts for
3 papers
cs.LG2019★ 1 cited
Not All Features Are Equal: Feature Leveling Deep Neural Networks for Better Interpretation
Yingjing Lu, Runde Yang
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.…
cs.CV2019★ 4 cited
The Level Weighted Structural Similarity Loss: A Step Away from the MSE
Yingjing Lu
The Mean Square Error (MSE) has shown its strength when applied in deep generative models such as Auto-Encoders to model reconstruction loss. However, in image domain especially, t…
cs.LG2018
Cross Domain Image Generation through Latent Space Exploration with Adversarial Loss
Yingjing Lu
Conditional domain generation is a good way to interactively control sample generation process of deep generative models. However, once a conditional generative model has been crea…