1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2025
Inverse Evolution Data Augmentation for Neural PDE Solvers
Chaoyu Liu, Chris Budd, Carola-Bibiane Schönlieb
Neural networks have emerged as promising tools for solving partial differential equations (PDEs), particularly through the application of neural operators. Training neural operato…
cs.LG2023★ 1 cited
Closing the ODE-SDE gap in score-based diffusion models through the Fokker-Planck equation
Teo Deveney, Jan Stanczuk, Lisa Maria Kreusser +2
Score-based diffusion models have emerged as one of the most promising frameworks for deep generative modelling, due to their state-of-the art performance in many generation tasks…