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cs.LG2024
DEFT: Efficient Fine-Tuning of Diffusion Models by Learning the Generalised -transform
Alexander Denker, Francisco Vargas, Shreyas Padhy +7
Generative modelling paradigms based on denoising diffusion processes have emerged as a leading candidate for conditional sampling in inverse problems. In many real-world applicati…
cs.LG2023
A framework for conditional diffusion modelling with applications in motif scaffolding for protein design
Kieran Didi, Francisco Vargas, Simon V Mathis +4
Many protein design applications, such as binder or enzyme design, require scaffolding a structural motif with high precision. Generative modelling paradigms based on denoising dif…