SOURCE-LINKED INTELLIGENCE

Direct Topology Tracking in Continuous Implicit Models

arXiv · AI, language, vision and robotics · article · Sep 10, 2026 · UTC

We present a framework for tracking topological features directly within continuous implicit models. Such models, including implicit neural representations (INRs) and multivariate functional approximations (MFAs), are increasingly adopted to represent scientific data without the resolution constraints of discrete grids. They offer compact, smooth, and differentiable representations of complex fields, enabling new opportunities for high-performance data storage, reconstruction, and analysis. Given a continuous implicit model, our method tracks the evolution of critical points by querying the mo

Read original source ↗ Open in workspace

recordType

paper

region

Global