NObSP: Functional Decomposition of Neural Networks via Oblique Subspace Projections
Results indicate that NObSP complements scalar attribution methods by recovering functional contribution profiles with separable positive and negative evidence.
2 papers indexed here
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Results indicate that NObSP complements scalar attribution methods by recovering functional contribution profiles with separable positive and negative evidence.
The core of the paper addresses two problems: the automatic generation of artificial blood cell images and the digital artificial staining to reduce inter-laboratory differences, and how generative Artificial Intelligence methods can help overcome obstacles.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.