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| CS 58700 - Foundations Of Deep Learning |
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Associated Term:
Spring 2024
Learning Outcomes: 1. Understand statistical Foundations of Deep Learning. 2. Understand feedforward Networks. 3. Understand stochastic optimization of neural network models. 4. Understand Bayesian Neural Networks. 5. Understand invariant & Equivariant Representation Learning. 6. Understand task-invariant representations. 7. Understand meta Learning. 8. Understand multi-task Learning. 9. Understand transfer Learning. 10. Understand implicit generative models (probabilistic models without explicit likelihoods). 11. Understand variational Auto-Encoders. 12. Understand generative Adversarial Networks. 13. Understand stable Diffusion Generative models. 14. Understand how to evaluate the performance of neural networks, as well as formulate and test hypotheses. 15. Understand how theory and algorithmic elements interact to impact performance. Required Materials: Technical Requirements: |
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