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cs.LG2026
One-Step Generative Modeling via Wasserstein Gradient Flows
Jiaqi Han, Puheng Li, Qiushan Guo +3
Diffusion models and flow-based methods have shown impressive generative capability, especially for images, but their sampling is expensive because it requires many iterative updat…
cs.LG2022★ 1 cited
Overparameterized ReLU Neural Networks Learn the Simplest Models: Neural Isometry and Exact Recovery
Yifei Wang, Yixuan Hua, Emmanuel Candés +1
The practice of deep learning has shown that neural networks generalize remarkably well even with an extreme number of learned parameters. This appears to contradict traditional st…