1. 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)
  2. 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)
  3. Accurate experimental band gap predictions with multifidelity correction learning
    P.-P. De Breuck, G. Heymans, G.-M. Rignanese
    J Mater. Inf. 2, 10 (2022)
  4. 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)
  5. 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)
  6. Vibrational properties of solids : a machine learning approach
    P.-P. De Breuck, G.-M. Rignanese
    Master Thesis (2019)