5 papers
Generative Video Compression with Adaptive Score Distillation
Naifu Xue, Zhaoyang Jia, Haosen Li +7
Diffusion models provide strong generative capabilities for video compression at ultra-low bitrates. Existing diffusion-based video codecs adapt base models originally developed fo…
Score Approximation for Diffusion Models on Arbitrary Low-Dimensional Structures
Xinhe Mu, Zaijiu Shang, Zhaoqi Zhou +4
The remarkable success of score-based diffusion models has spurred significant efforts to establish their theoretical foundations. However, existing complexity bounds for score app…
UniFluids: Unified Neural Operator Learning with Conditional Flow-matching
Haosen Li, Qi Meng, Jiahao Li +4
Partial differential equation (PDE) simulation holds extensive significance in scientific research. Currently, the integration of deep neural networks to learn solution operators o…
OmniFluids: Physics Pre-trained Modeling of Fluid Dynamics
Rui Zhang, Qi Meng, Han Wan +3
Computational fluid dynamics (CFD) drives progress in numerous scientific and engineering fields, yet high-fidelity simulations remain computationally prohibitive. While machine le…
Riemannian Neural Geodesic Interpolant
Jiawen Wu, Bingguang Chen, Yuyi Zhou +3
Stochastic interpolants are efficient generative models that bridge two arbitrary probability density functions in finite time, enabling flexible generation from the source to the…