mlsanityData to 14 Oct 2026

Reentrant value fields as delayed coupled reaction-diffusion systems on finite graphs

arXiv 2605.03940 ↗First posted 5 May 2026math.DS cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

We describe a dynamical system in which a symbolic field is coupled to a geometric field via a bipartite Hilbert-Schmidt kernel. The system is fully described by a retarded functional differential equation (RFDE) on the history space, subject to Lipschitz and small gain conditions. We show that the RFDE is well-posed under constant input and that it admits a compact global attractor. The principal subsystem (HL, XR, P), which is comprised of the two primary fields as well as an executive field, is shown to be globally stable independent of delay, provided that the interfield coupling satisfies CK2<μLμR. In addition, we describe design specifications that fulfill the hypotheses of the main Theorem.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 63 references that are in the map. First posted on arXiv 5 May 2026.

Builds on

12 of 63 references.

References · 12

  1. 2017Attention Is All You Needcited by 60,361
  2. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
  3. 2017Graph Attention Networkscited by 8,923
  4. 2016Layer Normalizationcited by 5,669
  5. 2018Spectral Normalization for Generative Adversarial Networkscited by 1,636
  6. 2018Relational inductive biases, deep learning, and graph networkscited by 1,360
  7. 2021Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gaugescited by 1,167
  8. 2020Mastering Atari with Discrete World Modelscited by 1,007
  9. 2021E(n) Equivariant Graph Neural Networkscited by 965
  10. 2020Object-Centric Learning with Slot Attentioncited by 876
  11. 2018Recurrent World Models Facilitate Policy Evolutioncited by 785
  12. 2016From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classificationcited by 341

Built on by

Not cited yet.