Code for the paper: Putting An End to End-to-End: Gradient-Isolated Learning of Representations
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Updated
Mar 28, 2023 - Python
Code for the paper: Putting An End to End-to-End: Gradient-Isolated Learning of Representations
A lightweight and flexible framework for Hebbian learning in PyTorch.
NGC-Learn: Neurobiological Learning and Biomimetic Systems Simulation in Python
Forward Pass Learning and Inference Library, for neural networks and general intelligence, Signal Propagation (sigprop)
Implementation/simulation of the predictive forward-forward credit assignment algorithm for training neurobiologically-plausible recurrent neural network models.
We introduce Local recurrent Predictive coding model termed as Parallel temporal Neural Coding Network. Unlike classical RNNs, our model is pure local and doesn't require computing gradients backward in time; thus computationally more efficient compared to BPTT and can be used for online learning
Deep Spiking Reinforcement Learning
Github page for SSDFA
A generative neural network with two streams to recognize externally generated optic flow
Programming coverage of the results presented in "Connectivity versus Entropy" by Y.S. Abu-Mostafa, 1988
A PyTorch implementation for the paper Deep Spike Learning with Local Classifiers
A predictive coding neural network to learn invariant representations from short video clips
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