11 citations · 14 across the 3 of their papers we have counts for
3 papers
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…
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…
Can Physics-Informed Neural Networks beat the Finite Element Method?
Tamara G. Grossmann, Urszula Julia Komorowska, Jonas Latz +1
Partial differential equations play a fundamental role in the mathematical modelling of many processes and systems in physical, biological and other sciences. To simulate such proc…