Author

V. Putkaradze

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Jul 2026

Latent Lie-Poisson Neural Networks (LLPNNs): Discovering the motion of Lie-Poisson systems through observable data and latent dynamics

Latent Lie--Poisson Neural Networks (LLPNNs), a structure-preserving framework for learning Lie--Poisson dynamics directly from observable data, which preserves the geometric structure and is applicable to both regular and degenerate Hamiltonian systems.

V. Putkaradze · Neural Networks · 0 citations

Preprint Aug 2026

The Neural Division of Labor: Biologically-Inspired Modular Architectures for Robust Neuromorphic Computing

A Decomposable Spiking Neural Network (D-SNN) is reported that eliminates global synaptic entanglement by structurally isolating classification pathways into independent experts, establishing an efficient foundation for deploying deterministic neuromorphic intelligence in resource-constrained edge environments.

Maksim Bazhenov, S. Grubas, V. Putkaradze · 0 citations