13 citations · 16 across the 3 of their papers we have counts for
3 papers
Learning to Grow Pretrained Models for Efficient Transformer Training
Peihao Wang, Rameswar Panda, Lucas Torroba Hennigen +6
Scaling transformers has led to significant breakthroughs in many domains, leading to a paradigm in which larger versions of existing models are trained and released on a periodic…
Neural Implicit Dictionary via Mixture-of-Expert Training
Peihao Wang, Zhiwen Fan, Tianlong Chen +1
Representing visual signals by coordinate-based deep fully-connected networks has been shown advantageous in fitting complex details and solving inverse problems than discrete grid…
Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations
Tianlong Chen, Peihao Wang, Zhiwen Fan +1
Neural Radiance Field (NeRF) regresses a neural parameterized scene by differentially rendering multi-view images with ground-truth supervision. However, when interpolating novel v…