2 papers
math.NA2026
Spatio-temporal Latent Denoising Diffusion Probabilistic Models for Reduced-order Modeling of Parametrized Dynamical Systems
Michiel Nikken, Nicolò Botteghi, Federico Califano +1
Many scientific problems require accurate modeling of complex physical phenomena, such as fluid dynamics or climate modeling. These phenomena often result in high-dimensional and t…
cs.RO2024
Denoising Diffusion Planner: Learning Complex Paths from Low-Quality Demonstrations
Michiel Nikken, Nicolò Botteghi, Wesley Roozing +1
Denoising Diffusion Probabilistic Models (DDPMs) are powerful generative deep learning models that have been very successful at image generation, and, very recently, in path planni…