4 papers · 1 filter
MarS-FM: Generative Modeling of Molecular Dynamics via Markov State Models
Kacper Kapuśniak, Cristian Gabellini, Michael Bronstein +2
Molecular Dynamics (MD) is a powerful computational microscope for probing protein functions. However, the need for fine-grained integration and the long timescales of biomolecular…
Self-Refining Training for Amortized Density Functional Theory
Majdi Hassan, Cristian Gabellini, Hatem Helal +2
Density Functional Theory (DFT) allows for predicting all the chemical and physical properties of molecular systems from first principles by finding an approximate solution to the…
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets
Dominique Beaini, Shenyang Huang, Joao Alex Cunha +32
Recently, pre-trained foundation models have enabled significant advancements in multiple fields. In molecular machine learning, however, where datasets are often hand-curated, and…
Gotta be SAFE: A New Framework for Molecular Design
Emmanuel Noutahi, Cristian Gabellini, Michael Craig +2
Traditional molecular string representations, such as SMILES, often pose challenges for AI-driven molecular design due to their non-sequential depiction of molecular substructures.…