1 citations · 1 across the 2 of their papers we have counts for
3 papers
Discriminative reconstruction via simultaneous dense and sparse coding
Abiy Tasissa, Emmanouil Theodosis, Bahareh Tolooshams +1
Discriminative features extracted from the sparse coding model have been shown to perform well for classification. Recent deep learning architectures have further improved reconstr…
Evaluating Sparse Autoencoders: From Shallow Design to Matching Pursuit
Valérie Costa, Thomas Fel, Ekdeep Singh Lubana +2
Sparse autoencoders (SAEs) have recently become central tools for interpretability, leveraging dictionary learning principles to extract sparse, interpretable features from neural…
From Flat to Hierarchical: Extracting Sparse Representations with Matching Pursuit
Valérie Costa, Thomas Fel, Ekdeep Singh Lubana +2
Motivated by the hypothesis that neural network representations encode abstract, interpretable features as linearly accessible, approximately orthogonal directions, sparse autoenco…