{"slug": "l-fno-lorentzian-fourier-neural-operator-for-stochastic-event-dynamics", "title": "L-FNO: Lorentzian Fourier Neural Operator for Stochastic Event Dynamics", "summary": "Researchers introduced the Lorentzian Fourier Neural Operator (L-FNO), a stochastic neural operator combining an FNO-style covariate path, Lorentzian spectral kernels, and likelihood-based training, to model rare, bursty, and self-exciting events. In evaluations on eight synthetic point-process benchmarks and three real-world datasets covering disease outbreak prediction and semiconductor fault detection, L-FNO improved event likelihood, calibration diagnostics, and rare-event detection over regression- and likelihood-based neural operator baselines.", "body_md": "arXiv:2608.13562v1 Announce Type: new\nAbstract: Modern operational systems face uncertainty even in routine conditions, where rare, bursty, and self-exciting events emerge from both exogenous covariates and endogenous event dynamics. Standard neural operators are typically trained as regression-style function-to-function models rather than conditional-intensity estimators, limiting their suitability for sparse event regimes. We introduce the Lorentzian Fourier Neural Operator (L-FNO), a stochastic neural operator that combines an FNO-style covariate path, Lorentzian spectral kernels for history-dependent excitation, and a likelihood-based training objective. We evaluate L-FNO on eight synthetic point-process benchmarks and three real-world datasets covering disease outbreak prediction and semiconductor fault or defect detection. L-FNO improves event likelihood, calibration diagnostics, and rare-event detection over regression- and likelihood-based neural operator baselines. These results show that structured spectral memory and likelihood-based learning provide effective inductive biases for neural operator models of stochastic event dynamics.", "url": "https://wpnews.pro/news/l-fno-lorentzian-fourier-neural-operator-for-stochastic-event-dynamics", "canonical_source": "https://arxiv.org/abs/2608.13562", "published_at": "2026-08-17 04:00:00+00:00", "updated_at": "2026-08-17 04:12:44.965188+00:00", "lang": "en", "topics": ["machine-learning", "artificial-intelligence"], "entities": ["Lorentzian Fourier Neural Operator", "FNO"], "alternates": {"html": "https://wpnews.pro/news/l-fno-lorentzian-fourier-neural-operator-for-stochastic-event-dynamics", "markdown": "https://wpnews.pro/news/l-fno-lorentzian-fourier-neural-operator-for-stochastic-event-dynamics.md", "text": "https://wpnews.pro/news/l-fno-lorentzian-fourier-neural-operator-for-stochastic-event-dynamics.txt", "jsonld": "https://wpnews.pro/news/l-fno-lorentzian-fourier-neural-operator-for-stochastic-event-dynamics.jsonld"}}