Standout Papers

A software framework for probabilistic sensitivity analysis for computationally expensive models 2016 2026 2019 2022 529
  1. A software framework for probabilistic sensitivity analysis for computationally expensive models (2016)
    N. Vu‐Bac, Tom Lahmer et al. Advances in Engineering Software

Immediate Impact

67 standout
Sub-graph 1 of 22

Citing Papers

Polymer composites with high thermal conductivity: Theory, simulation, structure and interfacial regulation
2024 Standout
Progress and Opportunities for Machine Learning in Materials and Processes of Additive Manufacturing
2024 Standout
2 intermediate papers

Works of N. Vu‐Bac being referenced

Stochastic integrated machine learning based multiscale approach for the prediction of the thermal conductivity in carbon nanotube reinforced polymeric composites
2022
A stochastic multiscale method for the prediction of the thermal conductivity of Polymer nanocomposites through hybrid machine learning algorithms
2021
and 4 more

Author Peers

Author Last Decade Papers Cites
N. Vu‐Bac 1067 239 603 934 25 2.3k
Khader M. Hamdia 1088 96 487 1004 24 2.5k
Mohammad Silani 1216 265 820 752 48 2.3k
Tom Lahmer 1228 152 465 1767 95 3.1k
Hongbing Fang 579 207 232 966 55 2.0k
Di Wu 1732 61 682 1532 97 2.9k
Rodrigue Desmorat 2162 149 852 742 80 3.0k
Pengfei Liu 1128 239 734 692 86 2.7k
L. M. Kachanov 1830 81 744 700 19 2.6k
Jun Liu 472 140 597 497 92 1.9k
Gun Jin Yun 717 419 531 879 141 2.7k

All Works

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2026