Custom implementations of backpropagation-free deep learning algorithms, rigorously benchmarked against tuned baselines with hardware-validated energy, time, memory, and CO₂e measurements.
Backpropagation-free Graph Neural Networks
Cerebrum — A predictive-coding, backprop-free, fully-local-plasticity, neuromorphic-targeted learning architecture.
0ns zero-copy, autograd-free hybrid guide layer (Pre-Transformer Packet Rectifier). Uses viscous Burgers' & Vorticity under FNG V3 to pre-rectify high-order skewness & stream clean tensor manifolds straight into LLM Attention.
Spectral Morphogenetic Resonance Networks (MoReNet). A zero-backprop, O(|E|) complexity, continuous learning AI framework based on Spectral Graph Theory and fluid dynamics.
Modified automatic differentiaton free Mono-forward algorithm
Backprop-free, layer-by-layer training of Differentiable Logic Gate Networks with zero discretization gap, adaptive depth, and incremental logic simplification
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