thesis's People
thesis's Issues
Modularize useful functions in a utils file
Read diffusion survey paper
Set up complete demo TTS system in docker container
Send first draft of goal document to supervisors
Prepare for Distilling AI event 13/10
Recommended Reading:
Book: Feature Engineering and Selection: A Practical Approach for Predictive Models by Max Kuhn and Kjell Johnson (Chapters 11-13)
Open Access: http://www.feat.engineering/index.html
More Academic Resources:
A Survey on Feature Selection: https://www.sciencedirect.com/science/article/pii/S1877050916313047
Höra av mig till Accenture
Try to visualize PyTorch model diagnostics
It would be useful to have some plots over gradient, saturation, etc (inspired by Karpathy 3) when training. Try to get some plots of this from a trained PyTorch model
Prepare for ML reading group 6/10
Get inference and training of other diffusion models working
Write base cover letter
Set up meeting with Maria to discuss direction
Get DiffWave inference working
Get Griffin Lim baseline working
Write first draft of background on Diffusion models
Run experiements with different beta schedules
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What models should be tested? Just diffwave or maybe WaveGrad, or PriorGrad.
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What schedules to be tested? What schedules do prior works use?
Get DiffWave training working in Colab
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