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In adaptive sampling methods, instead of conventional long MD simulations, multiple short simulations are run in parallel. Then, states from the resultant trajectories are selected according to some criterion to run the next round of simulations.
Dec 11, 2023
Apr 9, 2024 · In this work, we propose a deep learning method with two novel adaptive sampling schemes (I and II). In the two schemes, the data are generated actively with a ...
May 26, 2024 · Adaptive sampling is a strategic approach employed during the training of PINNs to dynamically select or reallocate sample points, aiming to boost the network's ...
Dec 28, 2023 · This is a repository associated with the paper "An adaptive sampling and domain learning strategy for multivariate function approximation on unknown ...
7 days ago · This method dynamically adds new training samples or data points based on certain criteria and information gained from the previous iterations [40].
Aug 15, 2023 · (14) Zhao, Z.; Li, Q. Adaptive Sampling Methods for Learning Dynamical Systems. In Proceedings of Mathematical and Scientific Machine Learning; PMLR, 2022; pp ...
May 1, 2024 · Abstract:The article introduces a method to learn dynamical systems that are governed by Euler--Lagrange equations from data. ... adaptive sampling techniques. We ...
Jul 24, 2023 · Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world ...
Nov 24, 2023 · We propose a novel adaptive sampling method that concentrates samples close to the areas showing high loss values.
Jun 24, 2024 · Traditional physics-based models are first-principled, explainable, and sample-efficient. However, they often rely on strong modeling assumptions and expensive ...