All news
Digital Twin

Critical Weather Scenario Screening Using Weather-to-Voltage Predictive Modeling

US & West ·

Relevant to DT products

Original headline
Critical Weather Scenario Screening Using Weather-to-Voltage (W2V) Predictive Modeling
Read the original: arXiv — Systems and Control (eess.SY)

Translation and summary are machine-generated from the source. The full article is not republished; its rights belong to the source.

Related

ModellingUS & West

Bayesian inference for agent-based models with 90% fewer simulations

The DF-NPE method combines learned time-series summaries with two conditional normalizing flows for synthetic-data generation and posterior estimation. It supplements direct simulations with synthetic training pairs and supports pooled and ordered training strategies. In two settings of the Brock-Hommes asset-pricing model it cuts direct simulations by 90% while achieving lower posterior discrepancy and runtime.

DT.ForecastarXiv — Multiagent Systems (cs.MA) ↗
ModellingUS & West

Adapting neural posterior estimators for agent-based model inference

Agent-based models in economics and social sciences represent heterogeneous behavior and interactions through simulations, while their likelihood is often intractable for parameter estimation. The work examines likelihood-free neural inference, notably neural posterior estimation with normalizing flows providing amortized Bayesian inference. It notes that a pre-trained estimator may become inaccurate when the target task changes and discusses adapting such estimators.

DT.ForecastarXiv — Multiagent Systems (cs.MA) ↗