ASIA uses an LLM-based coding agent to autonomously perform system identification, tested empirically on two benchmarks while noting limitations in transparency and reproducibility.
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Nonparametric Bayesian methods with Gaussian and Besov-Laplace priors achieve minimax-optimal posterior contraction rates for covariate-driven point process intensity estimation under increasing domain asymptotics with ergodic covariates.
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ASIA: an Autonomous System Identification Agent
ASIA uses an LLM-based coding agent to autonomously perform system identification, tested empirically on two benchmarks while noting limitations in transparency and reproducibility.
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Increasing domain asymptotics for covariate-based nonparametric Bayesian intensity estimation with Gaussian and Besov-Laplace priors
Nonparametric Bayesian methods with Gaussian and Besov-Laplace priors achieve minimax-optimal posterior contraction rates for covariate-driven point process intensity estimation under increasing domain asymptotics with ergodic covariates.