Search Results for author:
Found 2 papers, 0 papers with code
MRL: Learning to Mix with Attention and Convolutions
To achieve an efficient mix, we exploit the domain-wide receptive field provided by self-attention for regional-scale mixing and convolutional kernels restricted to local scale for local-scale mixing.
Ranked #1 on
Multi-tissue Nucleus Segmentation
on CoNSeP
Massively Distributed SGD: ImageNet/ResNet-50 Training in a Flash
Scaling the distributed deep learning to a massive GPU cluster level is challenging due to the instability of the large mini-batch training and the overhead of the gradient synchronization.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
