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cs.LG2026
Inference and learning in sparse autoencoders as natural gradient flow
Hadi Vafaii, Tejas Rao, David Chanin +6
Sparse autoencoders are widely used to uncover interpretable features in neural networks, yet reliable recovery remains difficult when features overlap or activate infrequently. Th…
cs.LG2024
Poisson Variational Autoencoder
Hadi Vafaii, Dekel Galor, Jacob L. Yates
Variational autoencoders (VAEs) employ Bayesian inference to interpret sensory inputs, mirroring processes that occur in primate vision across both ventral (Higgins et al., 2021) a…