Reimplementation of Geoffrey Hinton's Forward-Forward Algorithm
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Updated
Nov 15, 2023 - Python
Reimplementation of Geoffrey Hinton's Forward-Forward Algorithm
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)
PyTorch implementation of Hinton's FF Algorithm with hard negatives sampling
Forward-Forward Neural Networks Library based on PyTorch
Backprop-free learning study: spiking (LIF) neurons + Forward-Forward + JEPA + int4 QAT, with a full ablation notebook.
An implementation of Recurrent Forward-Forward from Hinton's paper, later ported to the spike domain using SnnTorch.
Two brains on one analog substrate from ~80% unsupervised SCFF bulk + ~20% closed-form SLDA namer: the math model for a forward-only, on-chip continual learner. Behavioral simulation, no silicon. Draft 6.0 = the "baby neocortex," validated across 11 phases.
Forward-Forward algorithm on MNIST
Backprop-free, layer-by-layer training of Differentiable Logic Gate Networks with zero discretization gap, adaptive depth, and incremental logic simplification
Code for "Cumulative-Goodness Free-Riding in Forward-Forward Networks: Real, Repairable, but Not Accuracy-Dominant" (NeurIPS 2026).
Forward-Forward and Hebbian competitive learning for time series anomaly detection, clustering, and representation learning
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