Failed on benchmark
2026
Quadratic center-manifold bottleneck
Replace a conventional linear decoder in an autoencoder or latent state-space model with an explicit quadratic manifold decoder, allowing a small latent vector to represent curved and transport-like state trajectories. Add a dynamics-aware invariance loss that penalizes the discrepancy between the time derivative of the quadratic manifold and the neural dynamics evaluated on that manifold.
Paper: Beyond linear subspaces: Nonlinear moment matching meets quadratic manifolds
arXiv:2608.19486