2.8k citations · 8.6k across the 72 of their papers we have counts for
5 papers · 1 filter
Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Model
Jincheng Zhong, Xiangcheng Zhang, Jianmin Wang +1
Recent advancements in diffusion models have revolutionized generative modeling. However, the impressive and vivid outputs they produce often come at the cost of significant model…
Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models
Xingzhuo Guo, Yu Zhang, Baixu Chen +3
Diffusion models have emerged as powerful generative frameworks by progressively adding noise to data through a forward process and then reversing this process to generate realisti…
TimesBERT: A BERT-Style Foundation Model for Time Series Understanding
Haoran Zhang, Yong Liu, Yunzhong Qiu +4
Time series analysis is crucial in diverse scenarios. Beyond forecasting, considerable real-world tasks are categorized into classification, imputation, and anomaly detection, unde…
Transolver++: An Accurate Neural Solver for PDEs on Million-Scale Geometries
Huakun Luo, Haixu Wu, Hang Zhou +4
Although deep models have been widely explored in solving partial differential equations (PDEs), previous works are primarily limited to data only with up to tens of thousands of m…
ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks
Yuezhou Ma, Haixu Wu, Hang Zhou +3
Physics-informed neural networks (PINNs) have earned high expectations in solving partial differential equations (PDEs), but their optimization usually faces thorny challenges due…