Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

Questions tagged [bottlenecks]

For questions about "bottlenecks" in dimensional reduction, typically in reference to Artificial Neural Networks and Autoencoders.

The bottleneck in a neural network is just a layer with less neurons then the layer below or above it. Having such a layer encourages the network to compress feature representations to best fit in the available space, in order to get the best loss during training.

Source: What is the concept of Tensorflow Bottlenecks? (SE:AI)

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What are "bottlenecks" in neural networks?

What are "bottlenecks" in the context of neural networks? This term is mentioned, for example, in this TensorFlow article, which also uses the term "bottleneck values". How does one calculate bottleneck values? How do these values help image…
Anurag Singh
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What are bottleneck features?

In the blog post Building powerful image classification models using very little data, bottleneck features are mentioned. What are the bottleneck features? Do they change with the architecture that is used? Are they the final output of convolutional…
Abhishek Bhatia
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Does bottleneck size matter in Disentangled Variational Autoencoders?

I suppose that picking an appropriate size for the bottleneck in Autoencoders is neither a trivial nor an intuitive task. After watching this video about VAEs, I've been wondering: Do disentangled VAEs solve this problem? After all, if the network…
fabs
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What does it mean by bottleneck and representational bottleneck in feedforward neural networks?

Consider the following paragraph from section 2: General Design Principles of the research paper titled Rethinking the Inception Architecture for Computer Vision Avoid representational bottlenecks, especially early in the network. Feed-forward…
hanugm
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Why does each row of data have the same bottleneck features in the Autoencoder after training?

I was training an autoencoder for anomaly detection and I wish to extract the bottleneck features of the encoder for K-NN. The model architecture is as such: class Autoencoder(torch.nn.Module): def __init__(self): super().__init__() …
Aengus
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Autoencoder: predictions missing for nodes in the bottleneck layer

I'm using tf.Keras to build a deep-fully connected autoencoder. My input dataset is a dataframe with shape (19947,), and the purpose of the autoencoder is to predict normalized gene expression values. They are continuous values that range from…
beerzy
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