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Fast Bayesian force fields from active learning and mapped Gaussian processes...
Gaussian process (GP) regression is one promising technique of constructing machine learning force fields with built-in uncertainty quantification, which can be used to monitor... -
Fast Bayesian force fields from active learning: study of inter-dimensional t...
Gaussian process (GP) regression is one promising technique of constructing machine learning force fields with built-in uncertainty quantification, which can be used to monitor... -
Fast Bayesian force fields from active learning: study of inter-dimensional t...
Gaussian process (GP) regression is one promising technique of constructing machine learning force fields with built-in uncertainty quantification, which can be used to monitor... -
A flexible, perfluorinated analogue of aluminum fumarate metal-organic framework
We report the synthesis of Al-TFS, a novel aluminum metal-organic framework (MOF) based on tetrafluorosuccinic acid (H₂TFS), of formula Al(OH)(TFS)·1.5H₂O, introducing a new... -
Training sets based on uncertainty estimates in the cluster-expansion method
Cluster expansion (CE) has gained an increasing level of popularity in recent years, and many strategies have been proposed for training and fitting the CE models to... -
Figure data publication: Finite-time performance of a cyclic two-dimensional ...
This data publication contains the figure data for Finite-time performance of a cyclic two-dimensional quantum Ising heat engine (https://arxiv.org/abs/2503.14089). *.svg... -
Reserach Data: THz-induced structural phase transition in hybrid perovskites ...
Research data measured during the TELBE beamtime in March 2022 for the proposal 21202600 (THz-induced structural phase transition in hybrid perovskites). PI: Heejae Kim,... -
Data publication: Cavity-mediated thermal control of metal-to-insulator trans...
Original datasets corresponding to the publication.
