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A layer-wise training method for the convolutional autoencoder is used in (Masci, Jonathan, et al. "Stacked convolutional auto-encoders for hierarchical feature extraction." Artificial Neural Networks…
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Sparse autoencoder is an autoencoder with additional constraint that most coefficients tend to be zero, as described here: http://deeplearning.stanford.edu/wiki/index.php/Autoencoders_and_Sparsity
I…
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Hello
I have read your paper entitled "Pedestrian Stride-Length Estimation Based on LSTM
and Denoising Autoencoders". This work is very interesting and important for me, and I would like to implemen…
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Hi,
I am trying to finetune Autoencoder of Stable Diffusion model.
Could you please provide the details of learning rate scheduler and optimizer ?
Thank you
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I have just read the paper and moved into the source code. I was wondering what they are "psi", "H", "iw", and "vec", "star"
Could you kindly provide a explanation?
Thank you very much!! :)
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Investigate modern research papers in this area.
Document for the group ideas for modelling techniques.
Start with 'Minimal viable model type' (that we can get started on asap), then move to more so…
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https://doi.org/10.5220/0006636401400145
> In the era of precision medicine and cancer genomics, data are being generated so quickly that it is difficult to fully appreciate the extent of what is d…
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Unread papers that might give a new idea:
- [ ] [Attention Augmented Convolutional Networks](https://arxiv.org/abs/1904.09925)
- [ ] [Instances as Queries](https://arxiv.org/abs/2105.01928)
- [x] [Se…
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Hello, I saw your paper :
Using autoencoders for session-based job recommendations
However, I have a question in the paper.
This formula returns top n sessions for given taget session. I think …
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Can you add a mechanism to specify the dimensions of input layers, so that one can see the layer dimensions propagated through the network? That would make netscope an extremely handy tool for designi…