Abstract: Physics-informed neural networks (PINNs) incorporate physical constraints into their loss functions, allowing them to efficiently solve Partial Differential Equations (PDEs). In this work, ...

Abstract: Recent advances in diffusion models (DMs)—such as few-step denoising and multi-modal conditioning—have significantly improved computational efficiency and functional flexibility, but they ...

🔥 We introduce a generic formulation of the exact inversion samplers, BELM. the general k-step BELM: $$\bar{\mathbf{x}}_{i-1} = \sum_{j=1}^{k} a_{i,j}\cdot \bar ...