Publications
Peer-reviewed papers, conference contributions, and preprints from our research team.
- Poster · DDC Europe 2024
Identifying novel CDK9 inhibitors by traditional virtual screening and AI-based approaches
Kyryl Popov, Natasha Kamerlin, Johanna Åberg, Emelie Andersson, Mahtab Azimi, Mattias Jönsson, Areej Khabut, Filip Paulsen, Vuslat Sayin, Johan Evenäs, Johan Gudmundsson, Michael Green, S. Jalil Mahdizadeh, Leif A. Eriksson, Tomas Friman, Christina Velasco, Oskar Alsing
A benchmark of AIChemy's equivariant deep probabilistic graph neural network against classic and alternative AI-based virtual screening on a 24,000-compound Enamine hinge-binder library, presented at DDC Europe 2024.
2024 - Preprint · arXiv
Borch: A Deep Universal Probabilistic Programming Language
Lewis Belcher, Johan Gudmundsson, Michael Green
A scalable deep universal probabilistic programming language built on PyTorch, supporting hierarchical Bayesian models and Bayesian neural networks with one-line conversion.
2022 - Journal · Applied Sciences
An Operational Image-Based Digital Twin for Large-Scale Structures
Hans-Henrik Benzon, Xiao Chen, Lewis Belcher, Oscar Castro, Kim Branner, Jesper Smit
A digital twin framework combining image-based inspection with physics-informed modeling for large-scale structures such as wind turbine blades.
2022
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