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Found 4 papers, 2 papers with code
Understanding Distributed Representations of Concepts in Deep Neural Networks without Supervision
Understanding intermediate representations of the concepts learned by deep learning classifiers is indispensable for interpreting general model behaviors.
Edge-oriented Implicit Neural Representation with Channel Tuning
In addition, we propose Edge-oriented Representation Network (EoREN) that can reconstruct the image with clear edges by fitting gradient information (Edge-oriented module).
Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks?
Even though Generative Adversarial Networks (GANs) have shown a remarkable ability to generate high-quality images, GANs do not always guarantee the generation of photorealistic images.
Interpretation of Deep Temporal Representations by Selective Visualization of Internally Activated Nodes
Recently deep neural networks demonstrate competitive performances in classification and regression tasks for many temporal or sequential data.
