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
NGC-Learn: Neurobiological Learning and Biomimetic Systems Simulation in Python
A lightweight and flexible framework for Hebbian learning in PyTorch.
Implementation/simulation of the predictive forward-forward credit assignment algorithm for training neurobiologically-plausible recurrent neural network models.
Forward Pass Learning and Inference Library, for neural networks and general intelligence, Signal Propagation (sigprop)
Deep Spiking Reinforcement Learning
Github page for SSDFA
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
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
A generative neural network with two streams to recognize externally generated optic flow
Code for NeurIPS 2024 paper "Only Strict Saddles in the Energy Landscape of Predictive Coding Networks?"
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