attractor-neural-network

The Controlled Dynamics Attractor Transformer (CDAT) combines a mixture von Mises-Fisher attention energy with a Hopfield refinement energy and CANN-inspired excitation-inhibition modulation, providing topology-constrained dynamical systems for stable inference. It achieves state-of-the-art performance on graph anomaly detection and classification benchmarks.