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Implementations of Neural Network models and training algorithms from scratch [WIP]

Models and Algos

  • Feedforward network of arbitrary size and activation functions

  • Backprop with arbitrary cost function

  • Feedback alignment based training for FNNs [1]

  • Recurrent network with arbitrary size and activtion functions

  • Backprop through time [WIP]

  • RNN traninng with feedback alignment [2]

Dependencies

Numpy and Matplotlib - planning to use JAX for some of the grad operations.

References

[1] Lillicrap, Timothy P., et al. Random synaptic feedback weights support error backpropagation for deep learning. Nature communications 7 (2016): 13276

[2] Murray, J. M. (2018). Local online learning in recurrent networks with random feedback. BioRxiv, 458570.

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Generic implementations of neural network models and training alogs from scratch

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