Suiren-1.0 is a family of three molecular foundation models (Base, Dimer, ConfAvg) pre-trained on 70M+ DFT samples and distilled to achieve claimed state-of-the-art performance on quantum property prediction tasks from 2D inputs.
Uni-qsar: an auto-ml tool for molecular property prediction.arXiv preprint arXiv:2304.12239
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Boltz2 co-folding representations match or exceed existing models on ADMET benchmarks, accelerate generative modeling, and improve sample efficiency in ligand optimization while being complementary to 3D, bioassay, and quantum-chemical supervision.
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Suiren-1.0 Technical Report: A Family of Molecular Foundation Models
Suiren-1.0 is a family of three molecular foundation models (Base, Dimer, ConfAvg) pre-trained on 70M+ DFT samples and distilled to achieve claimed state-of-the-art performance on quantum property prediction tasks from 2D inputs.
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A Systematic Evaluation of Co-folding Model Representations for Small-Molecule Learning
Boltz2 co-folding representations match or exceed existing models on ADMET benchmarks, accelerate generative modeling, and improve sample efficiency in ligand optimization while being complementary to 3D, bioassay, and quantum-chemical supervision.