Results 121 to 130 of about 75,461 (296)
Neural Architecture Search for Convolutional and Transformer Deep Neural Networks [PDF]
, 2023 Deep Neural Networks (DNN) have dominated computer vision tasks during the last decade. However, in recent years, the demand for highly customized deep neural networks has increased significantly, which has made manual design of architectures a tedious
Chen, Boyu
core
Xenes for Sustainable Energy: A Roadmap From First‐Principles Design to Practical Deployment
Advanced Materials Interfaces, EarlyView.Emerging 2D Xenes are advancing from theoretical predictions toward practical energy‐storage and conversion technologies through the integration of first‐principles modelling, experimental synthesis, electrochemical validation, and AI‐assisted materials design, enabling accelerated discovery of high‐performance and sustainable electrochemical systems ...
Onur Karaman, Ceren Karaman
wiley +1 more source
Federated Neural Architecture Search
, 2022 To preserve user privacy while enabling mobile intelligence, techniques have been proposed to train deep neural networks on decentralized data. However, training over decentralized data makes the design of neural architecture quite difficult as it ...
Bian, Kaigui +6 more
core
Neural Architecture Search for Explainable Networks
, 2023 One of the main challenges in machine learning is providing understandable explanations for complex models. Despite outperforming humans in many tasks, machine learning models are often treated as black boxes that are difficult to interpret. Post-hoc explanation methods have been developed to create interpretable surrogate models that explain the ...
Yaoman Li, Irwin King
openaire +1 more source
Posterior-Guided Neural Architecture Search
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 The emergence of neural architecture search (NAS) has greatly advanced the research on network design. Recent proposals such as gradient-based methods or one-shot approaches significantly boost the efficiency of NAS. In this paper, we formulate the NAS problem from a Bayesian perspective.
Yizhou Zhou +4 more
openaire +3 more sources
Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization
Advanced Materials Technologies, EarlyView.An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue +8 more
wiley +1 more source
Neural Architecture Search (NAS)
Neural Architecture Search ...
Ioannis Kourouklides
core +1 more source
Hierarchical neural architecture search for deep stereo matching
, 2023 To reduce the human efforts in neural network design, Neural Architecture Search (NAS) has been applied with remarkable success to various high-level vision tasks such as classification and semantic segmentation. The underlying idea for the NAS algorithm
Harandi, M +7 more
core
Advanced Materials Technologies, EarlyView.This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane +4 more
wiley +1 more source
Graph HyperNetworks for Neural Architecture Search
CoRR, 2018 ICLR ...
Chris Zhang 0001 +2 more
openaire +3 more sources