This release introduces several major new features and infrastructure improvements across training, simulation, and model components. New Features Added full support for periodic boundary conditions in simulation and training Added tracing of replica exchanges in parallel tempering simulations Added multi-scheduler training support for both HDF5 and PyTorch datasets Model & Architecture Updates Added support for regularized version of SchNet and PaiNN Added custom MACE interaction block with tanh gating Added support for generic regularized RBF class Added RegL1 loss Priors update Added ExpRepulsion Added cutoff-based repulsion for standard and exponential repulsion Improvements & Fixes Small updates, optimizations, and bug fixes across the codebase Recommended Update This release is strongly recommended for all users of MLCG. In addition to minor bug fixes and stability improvements, it introduces major new functionality including full PBC support, new prior models, new regularization options. Full Changelog: https://github.com/ClementiGroup/mlcg/compare/v0.1.3...v0.1.4