Neural encoding with affine feature response transforms
InNER'21: 10th International IEEE EMBS Conference on Neural Engineering
NER'21: 10th International IEEE EMBS Conference on Neural Engineering (4-6 May 2021)
Article in monograph or in proceedings
Display more detailsDisplay less details
SW OZ DCC AI
NER'21: 10th International IEEE EMBS Conference on Neural Engineering
SubjectCognitive artificial intelligence
We introduce affine feature response transforms (AFRT; 'e-fərt ) - a new family of neural encoding models based on spatial transformer networks (STNs). AFRT drastically simplifies the state-of-the-art neural encoding models by factorising receptive fields into a sequential affine component with five out-of-the-box interpretable parameters and response components with a small number of feature weights per voxel.
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.