4 papers
Chemical filters for ultra-high-throughput materials screening and generation
Kinga O. Mastej, Panyalak Detrattanawichai, Hyunsoo Park +3
Generative artificial intelligence is rapidly transforming materials design by enabling de novo exploration of immense chemical spaces. Yet a large proportion of AI-generated compo…
Substitution-Based Analysis of Structural Novelty for Generative Models of Materials
Masahiro Negishi, Aron Walsh
There has been rapid progress in generative artificial intelligence (AI) models for inorganic crystal design, which can efficiently generate large numbers of candidate compounds af…
Continuous SUN (Stable, Unique, and Novel) Metric for Generative Modeling of Inorganic Crystals
Masahiro Negishi, Hyunsoo Park, Kinga O. Mastej +1
To address pressing scientific challenges such as climate change, increasingly sophisticated generative models are being developed to efficiently sample the large chemical space of…
WILTing Trees: Interpreting the Distance Between MPNN Embeddings
Masahiro Negishi, Thomas Gärtner, Pascal Welke
We investigate the distance function learned by message passing neural networks (MPNNs) in specific tasks, aiming to capture the functional distance between prediction targets that…