Diffusion-based text-to-image models can generate impressive images, but they largely treat an image as a single, flat output, which makes precise editing of individual elements difficult. This proposal studies layered […]
Vision encoders have demonstrated significant performance gains in visual generation and multimodal reasoning. These improvements are primarily attributed to the scaling of data, model capacity, and compute. However, this progress […]
The Huerta Center is proud to present a brown bag presentation by Graduate Student Research Awardee Valeria Alonso Blanco. She will present on a qualitative study that explores how undocumented Latinx transfer students navigate institutional support, belonging, and barriers at a four-year Hispanic Serving Institution (HSI). Findings reveal gaps between institutional commitments and student […]
Diffusion-based generative models offer a principled framework for probabilistic forecasting, but we show they suffer from a fundamental spectral collapse when applied to turbulent flows. A Fourier-space analysis of the forward SDE reveals that the mode-wise signal-to-noise ratio decays monotonically in wavenumber for power-law spectra, rendering high-wavenumber content indistinguishable from noise. We reinterpret the noise […]