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Influence of roughness and coating on the rebound of droplets on fabrics
P. J. Cruz, P.-P. De Breuck, G.-M. Rignanese, K. Glinel, A. M. Jonas
Surfaces and Interfaces 36, 102524 (2023)
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A simple denoising approach to exploit multi-fidelity data for machine learning
materials properties
X. Liu, P.-P. De Breuck, L. Wang, G.-M. Rignanese
npj Comput. Mater. 8, 233 (2022)
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Accurate experimental band gap
predictions with multifidelity correction learning
P.-P. De Breuck, G. Heymans, G.-M. Rignanese
J Mater. Inf. 2, 10 (2022)
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Robust model benchmarking and bias-imbalance in data-driven materials science: a
case study on MODNet
P.-P. De Breuck, M. L. Evans, G.-M. Rignanese
J. Phys.: Condens. Matter 33, 404002 (2021)
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Materials property prediction for limited datasets enabled by feature selection and
joint learning with MODNet
P.-P. De Breuck, G. Hautier, G.-M. Rignanese
npj Comput. Mater. 7, 83 (2021)
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Vibrational properties of solids : a machine learning approach
P.-P. De Breuck, G.-M. Rignanese
Master Thesis (2019)