A generative neural network with two streams to recognize externally generated optic flow
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Updated
May 22, 2024 - Python
A generative neural network with two streams to recognize externally generated optic flow
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
Programming coverage of the results presented in "Connectivity versus Entropy" by Y.S. Abu-Mostafa, 1988
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
Github page for SSDFA
Deep Spiking Reinforcement Learning
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.
A lightweight and flexible framework for Hebbian learning in PyTorch.
NGC-Learn: Neurobiological Learning and Biomimetic Systems Simulation in Python
Code for the paper: Putting An End to End-to-End: Gradient-Isolated Learning of Representations
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