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Author

Grant M. Rotskoff

3 papers indexed here

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Preprint Sep 2026

Morphology and depletion force-based large-scale self-assembly of nanocubes on surface

Self-assembling nanoparticles is a highly efficient and facile way to form functional nano-, micro- and macrostructures. However, currently available methods lack precision and controllability in size, shape and composition, suffer from poor reproducibility and scalability, and require complex steps and expensive mater...

Yeonhee Lee, Seung-Sang Cha, Yuna Kwak et al. · 0 citations
#data science Preprint Sep 2026

FluxLite: Inference-Time Proposal Control for Discrete Diffusion Models

FluxLite is introduced, a lightweight, training-free proposal-control framework for discrete diffusion, identifying a tilted-path coverage factor that governs robustness to score error, together with finite-particle convergence for a fixed controlled Feynman-Kac recursion.

Yinuo Ren, Haoxuan Chen, Grant M. Rotskoff et al. · 1 citation
Open access Aug 2026

Efficient, Few-Shot Directed Evolution with Energy Rank Alignment.

Directed evolution is a powerful and widely used technique for protein engineering, and reducing the cost of iterated experimental observations has become a major priority for practitioners. A number of recent efforts to use machine-learning-based predictors to improve sequence selection have led to remarkable improvem...

Sebastian Ibarraran, Shriram Chennakesavalu, Frank Hu et al. · 0 citations

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