Can Physics-Informed Neural Networks beat the Finite Element Method? - Tamara G. Grossmann; Urszula Julia Komorowska; Jonas Latz; Carola-Bibiane Schönlieb (CoRR, 2023)

A framework for conditional diffusion modelling with applications in motif scaffolding for protein design. - Kieran Didi; Francisco Vargas 001; Simon V. Mathis; Vincent Dutordoir; Emile Mathieu; Urszula Julia Komorowska; Pietro Lio (CoRR, 2023)

Dynamics-Informed Protein Design with Structure Conditioning. - Urszula Julia Komorowska; Simon V. Mathis; Kieran Didi; Francisco Vargas 001; Pietro Lio; Mateja Jamnik (ICLR, 2024)

DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised $h$-transform. - Alexander Denker; Francisco Vargas 001; Shreyas Padhy; Kieran Didi; Simon V. Mathis; Riccardo Barbano; Vincent Dutordoir; Emile Mathieu; Urszula Julia Komorowska; Pietro Lió (NeurIPS, 2024)

DEFT: Efficient Finetuning of Conditional Diffusion Models by Learning the Generalised h-transform. - Alexander Denker; Francisco Vargas 001; Shreyas Padhy; Kieran Didi; Simon V. Mathis; Vincent Dutordoir; Riccardo Barbano; Emile Mathieu; Urszula Julia Komorowska; Pietro Lio (CoRR, 2024)