37 citations · 222 across the 43 of their papers we have counts for
45 papers
DiMOS: Doob-Guided Inference-Time Multi-Objective Search for Scientific Design
Ziqing Wang, Qijie Zhu, Weimin Wu +4
Scientific design often requires jointly satisfying multiple objectives and constraints. Pretrained masked diffusion models provide a generative foundation for this task, but fine-…
D-DOIT: Training-free Adaptation of Discrete Diffusion via Doob's h-Transform
Jieke Wu, Qijie Zhu, Weimin Wu +3
We propose D-DOIT (Discrete Doob-Oriented Inference-time Transformation), a training-free and efficient adaptation method for discrete diffusion models with generic rewards. D-DOIT…
Diffusion Models for Adaptive Sequential Data Generation
Haoyang Cao, Minshuo Chen, Yinbin Han +1
Generating realistic synthetic sequential data is critical in real-world applications across operations research, finance, healthcare, energy systems, and scientific computing, whe…
CreFlow: Corrective Reflow for Sparse-Reward Embodied Video Diffusion RL
Zhenyang Ni, Yijiang Li, Ruochen Jiao +7
Video generation models trained on heterogeneous data with likelihood-surrogate objectives can produce visually plausible rollouts that violate physical constraints in embodied man…
Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data
Hengyu Fu, Zehao Dou, Jiawei Guo +2
Diffusion Transformer, the backbone of Sora for video generation, successfully scales the capacity of diffusion models, pioneering new avenues for high-fidelity sequential data gen…
Provable Statistical Rates for Consistency Diffusion Models
Zehao Dou, Minshuo Chen, Mengdi Wang +1
Diffusion models have revolutionized various application domains, including computer vision and audio generation. Despite the state-of-the-art performance, diffusion models are kno…