The need for uncertainty quantification in machine-assisted medical decision making
Medicine, even from the earliest days of artificial intelligence (AI) research, has been one of
the most inspiring and promising domains for the application of AI-based approaches …
the most inspiring and promising domains for the application of AI-based approaches …
Graph hypernetworks for neural architecture search
Neural architecture search (NAS) automatically finds the best task-specific neural network
topology, outperforming many manual architecture designs. However, it can be prohibitively …
topology, outperforming many manual architecture designs. However, it can be prohibitively …
Towards efficient model compression via learned global ranking
Pruning convolutional filters has demonstrated its effectiveness in compressing ConvNets.
Prior art in filter pruning requires users to specify a target model complexity (eg, model size …
Prior art in filter pruning requires users to specify a target model complexity (eg, model size …