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- Intro & Overview
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Classroom Contents
Parameter Prediction for Unseen Deep Architectures - With First Author Boris Knyazev
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- 1 - Intro & Overview
- 2 - DeepNets-1M Dataset
- 3 - How to train the Hypernetwork
- 4 - Recap on Graph Neural Networks
- 5 - Message Passing mirrors forward and backward propagation
- 6 - How to deal with different output shapes
- 7 - Differentiable Normalization
- 8 - Virtual Residual Edges
- 9 - Meta-Batching
- 10 - Experimental Results
- 11 - Fine-Tuning experiments
- 12 - Public reception of the paper
- 13 - At , Boris mentions that they train the first variant, yet on closer examination, we decided it's more like the second
