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SwagCakes
SwagCakes
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I want to implement a Randomised Neural Network (alt. Neural Network with Random Weights (NNRW)) in keras based on the following paper: https://arxiv.org/pdf/2104.13669.pdf

Essentially the idea is the hidden layers are fixed randomly and only the output layer is optimized. (leading to a simple Least Squares solution).

I am familiar with using the Sequential API in keras to create models although I'm not sure how I would go about 'fixing' the hidden layers and only focus on optimising the output layer.

My last ditch attempt would be to simply code the network manually in NumPy, but I wanted to ask if anyone had any ideas on doing so in Tensorflow

I want to implement a Randomised Neural Network (alt. Neural Network with Random Weights (NNRW)) in keras based on the following paper: https://arxiv.org/pdf/2104.13669.pdf

Essentially the idea is the hidden layers are fixed randomly and only the output layer (leading to a simple Least Squares solution).

I am familiar with using the Sequential API in keras to create models although I'm not sure how I would go about 'fixing' the hidden layers and only focus on optimising the output layer.

My last ditch attempt would be to simply code the network manually in NumPy, but I wanted to ask if anyone had any ideas on doing so in Tensorflow

I want to implement a Randomised Neural Network (alt. Neural Network with Random Weights (NNRW)) in keras based on the following paper: https://arxiv.org/pdf/2104.13669.pdf

Essentially the idea is the hidden layers are fixed randomly and only the output layer is optimized. (leading to a simple Least Squares solution).

I am familiar with using the Sequential API in keras to create models although I'm not sure how I would go about 'fixing' the hidden layers and only focus on optimising the output layer.

My last ditch attempt would be to simply code the network manually in NumPy, but I wanted to ask if anyone had any ideas on doing so in Tensorflow

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SwagCakes
SwagCakes
  • 1
  • 1

Implementing a Randomized Neural Network using Tensorflow?

I want to implement a Randomised Neural Network (alt. Neural Network with Random Weights (NNRW)) in keras based on the following paper: https://arxiv.org/pdf/2104.13669.pdf

Essentially the idea is the hidden layers are fixed randomly and only the output layer (leading to a simple Least Squares solution).

I am familiar with using the Sequential API in keras to create models although I'm not sure how I would go about 'fixing' the hidden layers and only focus on optimising the output layer.

My last ditch attempt would be to simply code the network manually in NumPy, but I wanted to ask if anyone had any ideas on doing so in Tensorflow