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Classroom Contents
Self-Supervised Learning and Variational Inference
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- 1 – Welcome to class
- 2 – GANs revisited
- 3 – Self-supervised learning: a broader purpose
- 4 – Sparse modeling
- 5 – Amortized inference
- 6 – Convolutional sparse modeling with group sparsity
- 7 – Discriminant recurrent sparse AE
- 8 – Other self-supervised learning techniques
- 9 – Group sparsity
- 10 – Regularization through temporal consistency
- 11 – VAE: intuitive interpretation
- 12 – VAE: probabilistic variational approximation-based interpretation
