Topological Neural Dynamics: A Neuron-wise Framework for Sequence Modeling
Existing sequence models, including RNNs, LSTMs, continuous-time networks, and Transformers, share a common structural principle: layer-wise dynamics, where all neurons in the same layer co-evolve through a shared parameterized operator, leaving individual neurons no freedom to evolve independently. Yet in many complex dynamical systems, rich global behavior emerges precisely from locally evolving units interacting through structured connectivity. Inspired by this principle, we introduce Topological Neural Dynamics (TND), a sequence modeling framework that shifts computation from layer-wise to neuron-wise dynamics. TND represents a neural system as a directed neuron graph, an interaction ...
| Authors | Borui Cai, Yao Zhao |
|---|---|
| Primary category | cs.LG |
| Published | 19 June 2026 |
| Last updated at source | 7 July 2026 |
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