3 papers
physics.chem-ph2026
Low-rank approximation of Moment Tensor Potential enables reducing training set size without loss of accuracy
Anna Bondarenko, Nikita Rybin, Maxim Rakhuba +1
In this study, we implement a low-rank approximation of Moment Tensor Potential (MTP) based on the tensor train (TT) decomposition. The implemented tensor-factorized MTP (TFMTP) an…
cs.LG2026
Tensorion: A Tensor-Aware Generalization of the Muon Optimizer
Vladimir Bogachev, Vladimir Aletov, Alexander Molozhavenko +2
Common first-order optimizers, such as Adam, implicitly treat each parameter block as an unstructured vector, which disregards the multilinear weight structure present in many mode…
physics.chem-ph2025
Low-rank matrix and tensor approximations for compression of machine-learning interatomic potentials
Igor Vorotnikov, Fedor Romashov, Nikita Rybin +2
Machine-learning interatomic potentials (MLIPs) have become a mainstay in computationally-guided materials science, surpassing traditional force fields due to their flexible functi…