图像生成

NuiScene: Exploring Efficient Generation of Unbounded Outdoor Scenes

Han-Hung Lee, Qinghong Han, Angel X. Chang

机构 * Simon Fraser University（西蒙弗雷泽大学） 纠错

专题命中 效率与蒸馏 ：diffusion(abstract)；inpainting(abstract)；分类 cs.CV

Comments Project Page: \url{https://3dlg-hcvc.github.io/NuiScene/}

Data-Dependent Smoothing for Protein Discovery with Walk-Jump Sampling

Srinivas Anumasa, Barath Chandran. C, Tingting Chen, Dianbo Liu

机构 * National University of Singapore（新加坡国立大学） ； Indian Institute of Technology, Roorkee（印度理工学院罗尔克学院） 纠错

专题命中 效率与蒸馏 ：diffusion(abstract)

Efficient Bayesian Sampling with Langevin Birth-Death Dynamics

Alex Leviyev, Francesco Iacovelli, Aaron Zimmerman

专题命中 效率与蒸馏 ：diffusion(abstract)

Efficient Transformer-Inspired Variants of Physics-Informed Deep Operator Networks

Zhi-Feng Wei, Wenqian Chen, Panos Stinis

机构 * Pacific Northwest National Laboratory（太平洋西北国家实验室） ； University of Washington（华盛顿大学） ； Brown University（布朗大学） 纠错

专题命中 效率与蒸馏 ：diffusion(abstract)

Comments Code will be released upon acceptance

An efficient spline-based scheme on Shishkin-type meshes for solving singularly perturbed coupled systems with Robin boundary conditions

Kousalya Ramanujam, Vembu Shanthi

专题命中 效率与蒸馏 ：diffusion(abstract)

Comments 20 pages, 6 figures

Accurate and efficient machine learning interatomic potentials for finite temperature modeling of molecular crystals

Flaviano Della Pia, Benjamin X. Shi, Venkat Kapil, Andrea Zen, Dario Alfè, Angelos Michaelides

专题命中 效率与蒸馏 ：diffusion(abstract)

Comments Updated figure 1 with corrected energy errors

Journal ref Chem. Sci., 16, 11419-11433 (2025)

Sampling, Diffusions, and Stochastic Localization

Andrea Montanari

机构 * Department of Statistics and Department of Mathematics, Stanford University（统计学系和数学系，斯坦福大学） ； Granica Computing Inc（Granica计算公司） 纠错

专题命中 效率与蒸馏 ：diffusion(abstract)

Comments 38 pages, 5 pdf figures