3 papers
nucl-th2026
A Gaussian Process framework for constraining the nuclear equation of state from microscopic calculations with correlated uncertainties
Y. G. Lee, J. Kim, T. Zhao +1
We present constraints on the nuclear equation of state (EOS) from microscopic asymmetric matter calculations at zero temperature based on chiral nucleon-nucleon and three-nucleon…
nucl-th2026
Active learning emulators for nuclear two-body scattering in momentum space
A. Giri, J. Kim, C. Drischler +2
We extend the active learning emulators for two-body scattering in coordinate space with error estimation, recently developed by Maldonado et al. [Phys. Rev. C 112, 024002], to cou…
cs.AI2024
Reinforcement learning on structure-conditioned categorical diffusion for protein inverse folding
Yasha Ektefaie, Olivia Viessmann, Siddharth Narayanan +3
Protein inverse folding-that is, predicting an amino acid sequence that will fold into the desired 3D structure-is an important problem for structure-based protein design. Machine…