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Alzheimer's related dementia severity classification from magnetic resonance imaging using derivative-free optimization of convolutional neural network. [PDF]

Sci Rep
Ganesan SK, Velusamy P, Parthsarathy P, Vasudevan A.   +3 more
europepmc   +1 more source

Chimera: a block-based neural architecture search framework for event-based object detection. [PDF]

Front Artif Intell
Silva DA, Elsheikh A, Smagulova K, Fouda ME, Eltawil AM.   +4 more
europepmc   +1 more source

[Cluster-guided adaptive Transformer for muscle fatigue prediction]. [PDF]

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
Fan B, Bao X, Ding L, Wu J.
europepmc   +1 more source

Image classification optimization technology based on differentiable neural architecture search improvement model. [PDF]

PLoS One
Ji Y, Li W, Yu N.
europepmc   +1 more source

Polymer Concepts in Cellular Function

Advanced Science, EarlyView.
Miao Yu, Shikha Dhiman, Dorothee Dormann, Frauke Gräter, Katja Luck, Friederike Schmid, Andreas Walther, Edward A. Lemke   +7 more
wiley   +1 more source

An Efficient Evolutionary Neural Architecture Search Algorithm Without Training. [PDF]

Biomimetics (Basel)
An Y, Zhang C, Shao J, Yan Y, Sun B.
europepmc   +1 more source

Compositional neurosymbolic representations enable efficient active exploration. [PDF]

Nat Commun
Furlong PM, Dumont NS, Antonova R, Orchard J, Eliasmith C.   +4 more
europepmc   +1 more source

PRE-NAS: Evolutionary Neural Architecture Search With Predictor

IEEE Transactions on Evolutionary Computation, 2023
Neural architecture search (NAS) aims to automate architecture engineering in neural networks. This often requires a high computational overhead to evaluate a number of candidate networks from the set of all possible networks in the search space ...
Vic Ciesielski, Haytham M Fayek, Andy Song   +2 more
exaly   +4 more sources

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MIGO-NAS: Towards Fast and Generalizable Neural Architecture Search

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
Neural architecture search (NAS) has achieved unprecedented performance in various computer vision tasks. However, most existing NAS methods are defected in search efficiency and model generalizability. In this paper, we propose a novel NAS framework, termed MIGO-NAS, with the aim to guarantee the efficiency and generalizability in arbitrary search ...
Baochang Zhang, Rongrong Ji, Yonghong Tian   +2 more
exaly   +3 more sources

GP-NAS: Gaussian Process Based Neural Architecture Search

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020
Neural architecture search (NAS) advances beyond the state-of-the-art in various computer vision tasks by automating the designs of deep neural networks. In this paper, we aim to address three important questions in NAS: (1) How to measure the correlation between architectures and their performances?
Jiankang Deng, Ran He, Teng Xi
exaly   +2 more sources