Variational autoencoderLearned iterative shrinkage thresholding algorithmLearning rich data representations from unlabeled data is a key challenge towards applying deep learning algorithms in downstream tasks.
Reproducing the paper "Variational Sparse Coding" for the ICLR 2019 Reproducibility Challenge reproducible-researchpytorchunsupervised-learningsparse-codingiclrvariational-autoencoderdisentangled-representations UpdatedJul 6, 2023 Jupyter Notebook C and MATLAB implementation of CS recovery algorithm, i.e. Orthogon...
We propose a model based on variational auto-encoders (VAEs) in which interpretation is induced through latent space sparsity with a mixture of Spike and Slab distributions as prior. We derive an evidence lower bound for this model and propose a specific training method for recovering ...