7 citations · 9 across the 11 of their papers we have counts for
5 papers · 1 filter
Early-Bird Diffusion: Investigating and Leveraging Timestep-Aware Early-Bird Tickets in Diffusion Models for Efficient Training
Lexington Whalen, Zhenbang Du, Haoran You +4
Training diffusion models (DMs) requires substantial computational resources due to multiple forward and backward passes across numerous timesteps, motivating research into efficie…
Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling
Chaojian Li, Zhifan Ye, Massimiliano Lupo Pasini +4
Atomistic materials modeling is a critical task with wide-ranging applications, from drug discovery to materials science, where accurate predictions of the target material property…
GauRast: Enhancing GPU Triangle Rasterizers to Accelerate 3D Gaussian Splatting
Sixu Li, Ben Keller, Yingyan Celine Lin +1
3D intelligence leverages rich 3D features and stands as a promising frontier in AI, with 3D rendering fundamental to many downstream applications. 3D Gaussian Splatting (3DGS), an…
Uni-Render: A Unified Accelerator for Real-Time Rendering Across Diverse Neural Renderers
Chaojian Li, Sixu Li, Linrui Jiang +2
Recent advancements in neural rendering technologies and their supporting devices have paved the way for immersive 3D experiences, significantly transforming human interaction with…
Gaussian Blending Unit: An Edge GPU Plug-in for Real-Time Gaussian-Based Rendering in AR/VR
Zhifan Ye, Yonggan Fu, Jingqun Zhang +8
The rapidly advancing field of Augmented and Virtual Reality (AR/VR) demands real-time, photorealistic rendering on resource-constrained platforms. 3D Gaussian Splatting, deliverin…