3 citations · 5 across the 5 of their papers we have counts for
5 papers
Operator Flow Matching for Timeseries Forecasting
Yolanne Yi Ran Lee, Kyriakos Flouris
Forecasting high-dimensional, PDE-governed dynamics remains a core challenge for generative modeling. Existing autoregressive and diffusion-based approaches often suffer cumulative…
Localized FNO for Spatiotemporal Hemodynamic Upsampling in Aneurysm MRI
Kyriakos Flouris, Moritz Halter, Yolanne Y. R. Lee +6
Hemodynamic analysis is essential for predicting aneurysm rupture and guiding treatment. While magnetic resonance flow imaging enables time-resolved volumetric blood velocity measu…
Energy-Based Prior Latent Space Diffusion model for Reconstruction of Lumbar Vertebrae from Thick Slice MRI
Yanke Wang, Yolanne Y. R. Lee, Aurelio Dolfini +3
Lumbar spine problems are ubiquitous, motivating research into targeted imaging for treatment planning and guided interventions. While high resolution and high contrast CT has been…
Interpretable Neural PDE Solvers using Symbolic Frameworks
Yolanne Yi Ran Lee
Partial differential equations (PDEs) are ubiquitous in the world around us, modelling phenomena from heat and sound to quantum systems. Recent advances in deep learning have resul…
Autoregressive Renaissance in Neural PDE Solvers
Yolanne Yi Ran Lee
Recent developments in the field of neural partial differential equation (PDE) solvers have placed a strong emphasis on neural operators. However, the paper "Message Passing Neural…