1 citations · 1 across the 2 of their papers we have counts for
3 papers
HEDGEHOG: Hierarchical Evaluation of Drug Generators Through Rigorous Filtration
Daria A. Ryabchenko, Pavel Gurevich, Shamil Kadyrov +5
Generative molecular models can support early drug discovery by proposing new candidate compounds de novo. In practice, useful candidates must balance target-relevant activity, syn…
Matcha: Multi-Stage Riemannian Flow Matching for Accurate and Physically Valid Molecular Docking
Daria Frolova, Talgat Daulbaev, Egor Sevriugov +4
Accurate prediction of protein-ligand binding poses is crucial for structure-based drug design, yet existing methods struggle to balance speed, accuracy, and physical plausibility.…
Exploring Structure-Wise Uncertainty for 3D Medical Image Segmentation
Anton Vasiliuk, Daria Frolova, Mikhail Belyaev +1
When applying a Deep Learning model to medical images, it is crucial to estimate the model uncertainty. Voxel-wise uncertainty is a useful visual marker for human experts and could…