Results 91 to 100 of about 6,198,210 (289)

Neural Graph Embedding for Neural Architecture Search

Proceedings of the AAAI Conference on Artificial Intelligence, 2020
Existing neural architecture search (NAS) methods often operate in discrete or continuous spaces directly, which ignores the graphical topology knowledge of neural networks. This leads to suboptimal search performance and efficiency, given the factor that neural networks are essentially directed acyclic graphs (DAG).
Wei Li 0132, Shaogang Gong, Xiatian Zhu
openaire   +2 more sources

Beyond Visual Scoring: Computational Computed Tomography Analysis for High‐Resolution Computed Tomography–Based Quantification of Interstitial Lung Disease in Inflammatory Rheumatic Disease

Arthritis Care &Research, EarlyView.
Interstitial lung disease (ILD) is a significant cause of morbidity and mortality in patients with inflammatory rheumatic disorders (IRDs). High‐resolution computed tomography (HRCT) is widely considered the gold standard for the noninvasive assessment of ILD; however, its interpretation is constrained by substantial interobserver variability and the ...
Alexander Pfeil, Tobias Hoffmann, Ulf Teichgräber, Diane Renz, Denise Beckmann, Gunter Wolf, Nicole Schadewaldt, Bianca Lassen‐Schmidt   +7 more
wiley   +1 more source

GeNAS: Neural Architecture Search with Better Generalization

, 2023
Neural Architecture Search (NAS) aims to automatically excavate the optimal network architecture with superior test performance. Recent neural architecture search (NAS) approaches rely on validation loss or accuracy to find the superior network for the ...
Yu, Joonsang, Park, Geondo, Yoo, YoungJoon, Jeong, Joonhyun, Han, Dongyoon   +4 more
core  

Random Search and Reproducibility for Neural Architecture Search

CoRR, 2019
Neural architecture search (NAS) is a promising research direction that has the potential to replace expert-designed networks with learned, task-specific architectures. In this work, in order to help ground the empirical results in this field, we propose new NAS baselines that build off the following observations: (i) NAS is a specialized ...
Liam Li, Ameet Talwalkar
openaire   +4 more sources

Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane, Salama Makni, Mourad Kchaou, Ahmed El Hajjaji   +3 more
wiley   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Neural Architecture Search Algorithms for Quantum Autoencoders

IEEE Transactions on Quantum Engineering
The design of quantum circuits is currently driven by the specific objectives of the quantum algorithm in question. This approach thus relies on a significant manual effort by the quantum algorithm designer to design an appropriate circuit for the task ...
Ankit Kulshrestha, Xiaoyuan Liu, Ushijima-Mwesigwa Hayato, Ilya Safro   +3 more
doaj   +1 more source

A Numerical–Experimental Approach for Multi‐Matrix Fiber‐Reinforced Plastics Characterization Using Finite Element Model Updating

Advanced Engineering Materials, EarlyView.
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora, Tales V. Lisbôa, Axel Spickenheuer, Rogério J. Marczak, Jakson M. Vassoler   +4 more
wiley   +1 more source

HEC-NAS-FDS: hybrid expert-conditioned exhaustive neural network architecture search over finite design space

Scientific Reports
This article presents a new proof-of-concept method called Hybrid Expert-Conditioned Exhaustive Neural Network Architecture Search over Finite Design Space (HEC-NAS-FDS), which aims to find a suitable deep neural network (DNN) architecture with lower ...
Eva Holasova, Radek Fujdiak, Petr Mlynek
doaj   +1 more source

Overview of Differentiable Neural Network Architecture Search

Zhengzhou Daxue xuebao. Gongxue ban
Neural Architecture Search (NAS) was an interdisciplinary study in the field of deep learning, which aimed to automate the design of neural network structures. NAS required repeated training and evaluation of a large number of candidate networks, which
LU Peng, LI Keyan, ZHANG Hongpo, CHEN Liwei, WU Jiahui, LIU Shuaibing   +5 more
doaj   +1 more source