Bayesian Neural Networks¶
ToDos¶
- Get Baseline Models + Uncertainty
- Baseline NNs w. 1D Inputs
- Uncertainty
Baselines¶
This just means using some of the typical sklearn models and learning and doing predictions.
Baseline NNs w. 1D Inputs¶
We can base our work off of a recent paper (Code). They were able to use a 1D CNN architecture and got some good results. So let's replicate that!
SOTA Models w. DropOut¶
- VGG
- PreResNet
- Wide ResNet
- Tiramisu