1 citations · 1 across the 8 of their papers we have counts for
12 papers
Convergence of Denoising Diffusion Probabilistic Models: A Rényi Divergence Perspective
Wenliang Liu, Santiago Mazuelas, Guanding Yu +3
Denoising diffusion probabilistic models (DDPMs) have emerged as a powerful framework for generative modeling by transforming standard Gaussian inputs into outputs that approximate…
Consistent Distribution Matching for Data-Free Diffusion Distillation
Yuxiang Fu, Qi Yan, Zike Wu +4
Flow and diffusion models suffer from slow inference due to computationally expensive numerical integration. Distillation provides a promising way for a student model to learn from…
Score Augmentation for Diffusion Models
Liang Hou, Yuan Gao, Boyuan Jiang +6
Diffusion models have achieved remarkable success in generative modeling. However, this study confirms the existence of overfitting in diffusion model training, particularly in dat…
TrajFlow: Multi-modal Motion Prediction via Flow Matching
Qi Yan, Brian Zhang, Yutong Zhang +8
Efficient and accurate motion prediction is crucial for ensuring safety and informed decision-making in autonomous driving, particularly under dynamic real-world conditions that ne…
StreamSplat: Towards Online Dynamic 3D Reconstruction from Uncalibrated Video Streams
Zike Wu, Qi Yan, Xuanyu Yi +2
Real-time reconstruction of dynamic 3D scenes from uncalibrated video streams demands robust online methods that recover scene dynamics from sparse observations under strict latenc…
Neural MJD: Neural Non-Stationary Merton Jump Diffusion for Time Series Prediction
Yuanpei Gao, Qi Yan, Yan Leng +1
While deep learning methods have achieved strong performance in time series prediction, their black-box nature and inability to explicitly model underlying stochastic processes oft…
RETRO SYNFLOW: Discrete Flow Matching for Accurate and Diverse Single-Step Retrosynthesis
Robin Yadav, Qi Yan, Guy Wolf +2
A fundamental problem in organic chemistry is identifying and predicting the series of reactions that synthesize a desired target product molecule. Due to the combinatorial nature…
Leveraging MoE-based Large Language Model for Zero-Shot Multi-Task Semantic Communication
Sin-Yu Huang, Renjie Liao, Vincent W. S. Wong
Multi-task semantic communication (SC) can reduce the computational resources in wireless systems since retraining is not required when switching between tasks. However, existing a…
MoFlow: One-Step Flow Matching for Human Trajectory Forecasting via Implicit Maximum Likelihood Estimation based Distillation
Yuxiang Fu, Qi Yan, Lele Wang +2
In this paper, we address the problem of human trajectory forecasting, which aims to predict the inherently multi-modal future movements of humans based on their past trajectories…
Fréchet Video Motion Distance: A Metric for Evaluating Motion Consistency in Videos
Jiahe Liu, Youran Qu, Qi Yan +3
Significant advancements have been made in video generative models recently. Unlike image generation, video generation presents greater challenges, requiring not only generating hi…
An Information-Theoretic Framework for Out-of-Distribution Generalization with Applications to Stochastic Gradient Langevin Dynamics
Wenliang Liu, Guanding Yu, Lele Wang +1
We study the Out-of-Distribution (OOD) generalization in machine learning and propose a general framework that establishes information-theoretic generalization bounds. Our framewor…
Joint Generative Modeling of Grounded Scene Graphs and Images via Diffusion Models
Bicheng Xu, Qi Yan, Renjie Liao +2
We introduce a framework for joint grounded scene graph - image generation, a challenging task involving high-dimensional, multi-modal structured data. To effectively model this co…