NGC-Learn: Neurobiological Learning and Biomimetic Systems Simulation in Python
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Updated
Jun 4, 2024 - Python
NGC-Learn: Neurobiological Learning and Biomimetic Systems Simulation in Python
Predictive Coding in the Visual Cortex: a Functional Interpretation of Some Extra-classical Receptive-field Effects
PyHGF: A neural network library for predictive coding
Code from paper High-throughput Onboard Hyperspectral Image Compression with Ground-based CNN Reconstruction
Implementation/simulation of the predictive forward-forward credit assignment algorithm for training neurobiologically-plausible recurrent neural network models.
EIGen: Evolutionary Illusion Generator, based on predictive coding.
Deep Predictive Coding Network (PredNet) implemented with Chainer
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
Research of a deep predictive coding model for unsupervised representation learning from video and audio data.
Generalized Predictive Coding in Torch
Predictive coding networks for temporal prediction
Deep Local Predictive Coding Network (Local PCN) implemented with Chainer
Precision estimation and second-order prediction errors in cortical circuits
Regularization in Predictive Coding Networks; investigate the impact of dropout and several initializations on generalization capabilities
Predictive Coding (Rao & Ballard, 1999) Model
This repository has implementations of various alternatives to backpropagation for training neural networks.
Implementation/simulation of active neural generative coding (ANGC) for training neurobiologically-plausible active inference agent models.
Approximate Natural Gradient Descent with precision weighted predictive coding
NGC-Learn: Predictive Coding and Neurobiologically-Motivated Learning in Python
Recurrent spiking network models for predicting MNIST sequences
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