"sampling efficiency" Papers
23 papers found
Conference
Beyond Scores: Proximal Diffusion Models
Zhenghan Fang, Mateo Diaz, Sam Buchanan et al.
Convex Potential Mirror Langevin Algorithm for Efficient Sampling of Energy-Based Models
Zitao Yang, Amin Ullah, Shuai Li et al.
DeFoG: Discrete Flow Matching for Graph Generation
Yiming Qin, Manuel Madeira, Dorina Thanou et al.
Efficient Reinforcement Learning Through Adaptively Pretrained Visual Encoder
Yuhan Zhang, Guoqing Ma, Guangfu Hao et al.
Exploring the Design Space of Diffusion Bridge Models
Shaorong Zhang, Yuanbin Cheng, Greg Ver Steeg
Learning to Discretize Denoising Diffusion ODEs
Vinh Tong, Trung-Dung Hoang, Anji Liu et al.
Masked Diffusion Models as Energy Minimization
Sitong Chen, Shen Nie, Jiacheng Sun et al.
MRO: Enhancing Reasoning in Diffusion Language Models via Multi-Reward Optimization
Chenglong Wang, Yang Gan, Hang Zhou et al.
PatchScaler: An Efficient Patch-Independent Diffusion Model for Image Super-Resolution
Yong Liu, Hang Dong, Jinshan Pan et al.
Path Gradients after Flow Matching
Lorenz Vaitl, Leon Klein
PFDiff: Training-Free Acceleration of Diffusion Models Combining Past and Future Scores
Guangyi Wang, Yuren Cai, lijiang Li et al.
PID-controlled Langevin Dynamics for Faster Sampling on Generative Models
Hongyi Chen, Jianhai Shu, Jingtao Ding et al.
RayFlow: Instance-Aware Diffusion Acceleration via Adaptive Flow Trajectories
Huiyang Shao, Xin Xia, Yuhong Yang et al.
Schedule On the Fly: Diffusion Time Prediction for Faster and Better Image Generation
Zilyu Ye, Zhiyang Chen, Tiancheng Li et al.
Step-by-Step Reasoning for Math Problems via Twisted Sequential Monte Carlo
Shengyu Feng, Xiang Kong, shuang ma et al.
Straight-Line Diffusion Model for Efficient 3D Molecular Generation
Yuyan Ni, Shikun Feng, Haohan Chi et al.
Straightness of Rectified Flow: A Theoretical Insight into Wasserstein Convergence
Saptarshi Roy, Vansh Bansal, Purnamrita Sarkar et al.
TADA: Improved Diffusion Sampling with Training-free Augmented DynAmics
Tianrong Chen, Huangjie Zheng, David Berthelot et al.
Accelerating Neural Field Training via Soft Mining
Shakiba Kheradmand, Daniel Rebain, Gopal Sharma et al.
DC-Solver: Improving Predictor-Corrector Diffusion Sampler via Dynamic Compensation
Wenliang Zhao, Haolin Wang, Jie Zhou et al.
Fixed Point Diffusion Models
Luke Melas-Kyriazi, Xingjian Bai
Learning to Explore for Stochastic Gradient MCMC
SeungHyun Kim, Seohyeon Jung, SeongHyeon Kim et al.
Switched Flow Matching: Eliminating Singularities via Switching ODEs
Qunxi Zhu, Wei Lin