Author

Denis Blessing

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Preprint Aug 2026

JANUS: A Multi-modal Foundation Neural Sampler for Disordered Materials

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 disordered materials.

Denis Blessing, Mouyang Cheng, M. Schebek et al. · 0 citations

Preprint Jul 2026

ATLAS: A Foundation Neural Sampler for Amorphous Materials

LATAS, an efficient sampler that learns a diffusion process to generate Boltzmann-distributed amorphous structures directly from a target energy function, is introduced, establishing ATLAS as a foundation model for sampling, steering and designing amorphous materials.

Mouyang Cheng, Denis Blessing, Botao Yu et al. · 1 citation