15 citations · 51 across the 8 of their papers we have counts for
8 papers
Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition
Sihyun Yu, Weili Nie, De-An Huang +3
Video diffusion models have recently made great progress in generation quality, but are still limited by the high memory and computational requirements. This is because current vid…
T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching
Zizheng Pan, Bohan Zhuang, De-An Huang +5
Sampling from diffusion probabilistic models (DPMs) is often expensive for high-quality image generation and typically requires many steps with a large model. In this paper, we int…
Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled
Shengchao Liu, Chengpeng Wang, Jiarui Lu +5
Deep generative models (DGMs) have been widely developed for graph data. However, much less investigation has been carried out on understanding the latent space of such pretrained…
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies
Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang +89
In the upcoming decade, deep learning may revolutionize the natural sciences, enhancing our capacity to model and predict natural occurrences. This could herald a new era of scient…
Defending against Adversarial Audio via Diffusion Model
Shutong Wu, Jiongxiao Wang, Wei Ping +2
Deep learning models have been widely used in commercial acoustic systems in recent years. However, adversarial audio examples can cause abnormal behaviors for those acoustic syste…
ISB: Image-to-Image Schrödinger Bridge
Guan-Horng Liu, Arash Vahdat, De-An Huang +3
We propose Image-to-Image Schrödinger Bridge (ISB), a new class of conditional diffusion models that directly learn the nonlinear diffusion processes between two given distribu…