3 citations · 3 across the 2 of their papers we have counts for
2 papers
physics.chem-ph2026
Rem3Di: Learning smooth, chiral 3D molecular descriptors from atomistic foundation models
Steffen Wedig, Felix Burton, Rokas Elijošius +2
Foundation machine-learned interatomic potentials (MLIPs) are trained on large quantum-mechanical datasets and generalise across broad regions of chemical and configurational space…
physics.chem-ph2024★ 3 cited
Zero Shot Molecular Generation via Similarity Kernels
Rokas Elijošius, Fabian Zills, Ilyes Batatia +4
Generative modelling aims to accelerate the discovery of novel chemicals by directly proposing structures with desirable properties. Recently, score-based, or diffusion, generative…