4 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.CV2023★ 2 cited
ES-MVSNet: Efficient Framework for End-to-end Self-supervised Multi-View Stereo
Qiang Zhou, Chaohui Yu, Jingliang Li +3
Compared to the multi-stage self-supervised multi-view stereo (MVS) method, the end-to-end (E2E) approach has received more attention due to its concise and efficient training pipe…
cs.DC2022★ 4 cited
Boosting Distributed Training Performance of the Unpadded BERT Model
Jinle Zeng, Min Li, Zhihua Wu +4
Pre-training models are an important tool in Natural Language Processing (NLP), while the BERT model is a classic pre-training model whose structure has been widely adopted by foll…
cs.LG2022★ 2 cited
Nebula-I: A General Framework for Collaboratively Training Deep Learning Models on Low-Bandwidth Cloud Clusters
Yang Xiang, Zhihua Wu, Weibao Gong +15
The ever-growing model size and scale of compute have attracted increasing interests in training deep learning models over multiple nodes. However, when it comes to training on clo…