3 papers
cs.LG2025
Are We Really Learning the Score Function? Reinterpreting Diffusion Models Through Wasserstein Gradient Flow Matching
An B. Vuong, Michael T. McCann, Javier E. Santos +1
Diffusion models are commonly interpreted as learning the score function, i.e., the gradient of the log-density of noisy data. However, this assumption implies that the target of l…
cs.GR2025
Discrete Spatial Diffusion: Intensity-Preserving Diffusion Modeling
Javier E. Santos, Agnese Marcato, Roman Colman +2
Generative diffusion models have achieved remarkable success in producing high-quality images. However, these models typically operate in continuous intensity spaces, diffusing ind…
physics.geo-ph2024
Developing a Foundation Model for Predicting Material Failure
Agnese Marcato, Javier E. Santos, Aleksandra Pachalieva +10
Understanding material failure is critical for designing stronger and lighter structures by identifying weaknesses that could be mitigated. Existing full-physics numerical simulati…