3 citations · 6 across the 8 of their papers we have counts for
3 papers · 1 filter
Graph is all you need? Lightweight data-agnostic neural architecture search without training
Zhenhan Huang, Tejaswini Pedapati, Pin-Yu Chen +2
Neural architecture search (NAS) enables the automatic design of neural network models. However, training the candidates generated by the search algorithm for performance evaluatio…
Neural Capacitance: A New Perspective of Neural Network Selection via Edge Dynamics
Chunheng Jiang, Tejaswini Pedapati, Pin-Yu Chen +2
Efficient model selection for identifying a suitable pre-trained neural network to a downstream task is a fundamental yet challenging task in deep learning. Current practice requir…
Network Graph Based Neural Architecture Search
Zhenhan Huang, Chunheng Jiang, Pin-Yu Chen +1
Neural architecture search enables automation of architecture design. Despite its success, it is computationally costly and does not provide an insight on how to design a desirable…