3 citations · 3 across the 1 of their papers we have counts for
3 papers
Scalable and Cost-Efficient de Novo Template-Based Molecular Generation
Piotr Gaiński, Oussama Boussif, Andrei Rekesh +5
Template-based molecular generation offers a promising avenue for drug design by ensuring generated compounds are synthetically accessible through predefined reaction templates and…
ChiENN: Embracing Molecular Chirality with Graph Neural Networks
Piotr Gaiński, Michał Koziarski, Jacek Tabor +1
Graph Neural Networks (GNNs) play a fundamental role in many deep learning problems, in particular in cheminformatics. However, typical GNNs cannot capture the concept of chirality…
Relative Molecule Self-Attention Transformer
Łukasz Maziarka, Dawid Majchrowski, Tomasz Danel +5
Self-supervised learning holds promise to revolutionize molecule property prediction - a central task to drug discovery and many more industries - by enabling data efficient learni…