We develop a finite element method (FEM) for partial differential equation (PDE) solver based on the entanglement-basis representation introduced in our companion work. By lifting non-linear finite-element equations into an augmented coefficient space, the governing PDE together with boundary, initial, and inter-elemen...
Abhijatmedhi Chotrattanapituk, Michael J. Landry, Chu-Liang Fu et al.· 0 citations
CrysVCD is a modular framework that integrates chemical rules directly into the generative process, enabling orders-of-magnitude more efficient chemical valence checking compared with pure data-driven approaches with post-screening.
Diffusion-based deep generative models have emerged as powerful tools for inverse materials design. Yet many existing approaches overlook essential chemical constraints, such as oxidation-state balance, which can lead to chemically invalid structures. Here we introduce 'crystal generator with valence-constrained design...
JANUS is a multimodal neural sampler that couples continuous and masked discrete diffusion through an equivariant graph neural network trained directly from energy evaluations, without pre-generated equilibrium data, providing a foundation for thermodynamic sampling, characterization and inverse design of chemically di...
Denis Blessing, Mou-Yang Cheng, M. Schebek et al.· 2 citations
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