Jeriek Van den Abeele

• Buckley, Andy; Kvellestad, Anders; Raklev, Are; Scott, Pat; Sparre, Jon Vegard & Van den Abeele, Jeriek Paul [Vis alle 7 forfattere av denne artikkelen] (2020). Xsec: the cross-section evaluation code. European Physical Journal C. ISSN 1434-6044. 80(12). doi: 10.1140/epjc/s10052-020-08635-y. Fulltekst i vitenarkiv
• Van den Abeele, Jeriek Paul (2020). Illuminating elite patches of chemical space. Chemical Science. ISSN 2041-6520. 11(42), s. 11485–11491. doi: 10.1039/d0sc03544k. Vis sammendrag

  In the past few years, there has been considerable activity in both academic and industrial research to develop innovative machine learning approaches to locate novel, high-performing molecules in chemical space. Here we describe a new and fundamentally different type of approach that provides a holistic overview of how high-performing molecules are distributed throughout a search space. Based on an open-source, graph-based implementation [J. H. Jensen, Chem. Sci., 2019, 10, 3567–3572] of a traditional genetic algorithm for molecular optimisation, and influenced by state-of-the-art concepts from soft robot design [J. B. Mouret and J. Clune, Proceedings of the Artificial Life Conference, 2012, pp. 593–594], we provide an algorithm that (i) produces a large diversity of high-performing, yet qualitatively different molecules, (ii) illuminates the distribution of optimal solutions, and (iii) improves search efficiency compared to both machine learning and traditional genetic algorithm approaches.

• De Angelis, Alessandro; Tatischeff, Vincent; Grenier, Isabelle A.; McEnery, Julie E.; Mallamaci, Manuela & Tavani, Marco [Vis alle 51 forfattere av denne artikkelen] (2018). Science with e-ASTROGAM: A space mission for MeV–GeV gamma-ray astrophysics. Journal of High Energy Astrophysics. ISSN 2214-4048. 19, s. 1–106. doi: 10.1016/j.jheap.2018.07.001.

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