NewEvery arXiv paper, its researchers & institutions — mapped.
the archive

#surrogate modeling

4 results
physics.comp-ph2019

A distributed active subspace method for scalable surrogate modeling of function valued outputs

Hayley Guy, Alen Alexanderian, Meilin Yu

The paper proposes a distributed active subspace technique that combines adjoint‑based gradient computation with truncated Karhunen–Loève expansions to build scalable surrogate mod…

#active subspace#surrogate modeling#karhunen–loève expansion#dimension reduction
cs.NE2019

Benchmarking Surrogate-Assisted Genetic Recommender Systems

Thomas Gabor, Philipp Altmann

The paper introduces a recommender system that uses a surrogate model within an interactive genetic algorithm to suggest items, updating the model based on user feedback and showin…

#recommender systems#genetic algorithms#surrogate modeling#interactive evolution
math.NA2019

A hierarchical neural hybrid method for failure probability estimation

Ke Li, Kejun Tang, Jinglai Li +2

The paper proposes a hierarchical neural hybrid method that uses multifidelity neural network surrogates to efficiently estimate rare failure probabilities in high‑dimensional PDE‑…

#failure probability#surrogate modeling#neural networks#multifidelity
stat.ML2019

Towards Scalable Gaussian Process Modeling

Piyush Pandita, Jesper Kristensen, Liping Wang

The paper introduces an Adaptive Sequential Monte Carlo method to train Gaussian Process hyperparameters, enabling scalable surrogate modeling for large industrial datasets without…

#gaussian processes#surrogate modeling#bayesian inference#sequential monte carlo