# MFNets: data efficient all-at-once learning of multifidelity surrogates as directed networks of information sources

@article{Gorodetsky2020MFNetsDE, title={MFNets: data efficient all-at-once learning of multifidelity surrogates as directed networks of information sources}, author={Alex Arkady Gorodetsky and John D. Jakeman and Gianluca Geraci}, journal={Computational Mechanics}, year={2020}, volume={68}, pages={741 - 758} }

We present an approach for constructing a surrogate from ensembles of information sources of varying cost and accuracy. The multifidelity surrogate encodes connections between information sources as a directed acyclic graph, and is trained via gradient-based minimization of a nonlinear least squares objective. While the vast majority of state-of-the-art assumes hierarchical connections between information sources, our approach works with flexibly structured information sources that may not…

## 7 Citations

### Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification

- Computer ScienceArXiv
- 2022

The proposed context-aware multi-ﬁdelity Monte Carlo method applies to hierarchies of a wide range of types of low-⬁Delity models such as sparse-grid and deep-network models and takes into account the context in which the learning models will be used in upstream tasks.

### General multi-fidelity surrogate models: Framework and active learning strategies for efficient rare event simulation

- Computer ScienceArXiv
- 2022

A robust multi-fidelity surrogate modeling strategy in which the multi- fidelity surrogate is assembled using an active learning strategy using an on-the-fly model adequacy assessment set within a subset simulation framework for efficient reliability analysis is presented.

### Efficient Multifidelity Likelihood-Free Bayesian Inference with Adaptive Computational Resource Allocation

- Computer Science
- 2021

This work provides an adaptive multifidelity likelihood-free inference algorithm that learns the relationships between models at different fidelities and adapts resource allocation accordingly, and demonstrates that this algorithm produces posterior estimates with near-optimal efficiency.

### Improving Bayesian networks multifidelity surrogate construction with basis adaptation

- Computer ScienceAIAA SCITECH 2023 Forum
- 2023

### The Model Forest Ensemble Kalman Filter

- Computer Science, Environmental ScienceArXiv
- 2022

A possible way to make use of this collection of models in data assimilation by generalizing the idea of model hierarchies into model forests—collections of high and low ﬁdelity models organized in a groping of model trees such as to capture various relationships between diﬀerent models.

### Learning finite element convergence with the Multi-fidelity Graph Neural Network

- Computer ScienceComputer Methods in Applied Mechanics and Engineering
- 2022

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