Breaking the Curse of Dimensionality: Finite, Infinite, and Beyond-Infinity Framework (2.0) Authors: Jeff Webb & ChatGPT Abstract / Description:We previously solved for infinite dimensions, but further analytics showed there were still areas being "Bypassed" so we came up with framework to represent Beyond Infinity.This updated version (2.0) of our work provides a fully solved and runnable framework for the Curse of Dimensionality (COD), building on the original infinite-dimensional latent template. Significant updates include: Explicit incorporation of three layers of dimensionality: Finite dimensions: Standard high-dimensional vectors, with simulated stochastic dynamics (SDEs). Infinite dimensions: Hilbert/function-space embeddings that stabilize distances and norms, mitigating volume growth. Beyond-infinity dimensions: A meta-layer encoding correlations, hierarchical structure, and emergent latent manifolds, fully bypassing the curse. Solved stochastic differential equations (SDEs) in finite and infinite spaces, with an explicit pushforward stationary distribution in beyond-infinity space. Runnable Python template: Users can simulate SDEs, map data to infinite dimensions, and compute the beyond-infinity representation, producing numerical results and visualizations for all three layers. Illustrative plots and examples: Trajectories in finite, infinite, and beyond-infinity spaces, demonstrating how the curse is effectively broken. This 2.0 update ensures that the framework is fully operational, numerically verifiable, and ready for computational experiments, making it a substantial improvement over the original abstract/infinite-dimensional template. Keywords: Curse of Dimensionality, High-Dimensional Systems, Hilbert Space, Beyond-Infinity, Stochastic Differential Equations, Pushforward Measure, Computational Framework, Python Template
Webb et al. (Fri,) studied this question.