Augmenting genetic algorithms with machine learning for inverse molecular design von Kneiding, Hannes, Balcells, David

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Discovering metal complexes in vast chemical spaces

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Directional multiobjective optimization of metal complexes at the billion-system scale von Kneiding, Hannes, Nova, Ainara, Balcells, David

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Complex Learning: Machine learning approaches for transition metal complexes von Kneiding, Hannes

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AABBA Graph Kernel: Atom-Atom, Bond-Bond, and Bond-Atom Autocorrelations for Machine Learning von Morán-González, Lucía, Betten, Jørn Eirik, Kneiding, Hannes, Balcells, David

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Deep learning metal complex properties with natural quantum graphs von Kneiding, Hannes, Lukin, Ruslan, Lang, Lucas, Reine, Simen, Pedersen, Thomas Bondo, De Bin, Riccardo, Balcells, David

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Directional Multiobjective Optimization of Metal Complexes at the Billion-Scale with the tmQMg-L Dataset and PL-MOGA Algorithm von Kneiding, Hannes, Nova Flores, Ainara, Balcells Badia, David

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tmQMg-L von Kneiding, Hannes, Balcells, David, Nova, Ainara

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