A deep learning-based approach for the identification of a multi-parameter bwbn model
HIGHLIGHTS who: Zele Li et al. from the School of Civil Engineering, Southeast University, Nanjing, China have published the research: […]
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HIGHLIGHTS who: Lu00facia from the (UNIVERSITY) have published the paper: v, in the Journal: (JOURNAL) SUMMARY SILVA, LUPINACCI, STEFANUTO para
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Selective layer tuning and performance study of pre-trained models using genetic algorithm
HIGHLIGHTS who: Jae-Cheol Jeong et al. from the Department of Biomedical Engineering, Chonnam National University Hospital, Gwangju, Korea have published
Computer_Science
Acta chim. slov. 2022, 69, 304-315 vaghela and nath: modelling and multi-objective optimization ..
HIGHLIGHTS who: Acta Chim. Slov. and collaborators from the Department of Chemical Engineering, Government Engineering College (Affiliated t Gujarat Technological
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Evaluation of water flux predictive models developed using eddy-covariance observations and machine learning: a meta-analysis
HIGHLIGHTS who: Hydrol. Earth Syst. Sci. and colleagues from the Sciences, u00dcru00fcmqi, Xinjiang, China , College of Resources and Environment,
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On decoding strategies for neural text generators
HIGHLIGHTS who: Gian Wiher et al. from the ETH Zuu0308rich, Switzerland have published the Article: On Decoding Strategies for Neural
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Diff-explainer: differentiable convex optimization for explainable multi-hop inference
HIGHLIGHTS who: Explainable Multi-hop Inference and collaborators from the DepartmentUniversity of have published the paper: Diff-Explainer: Differentiable Convex Optimization for
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Review of automatic processing of topography and surface feature identification lidar data using machine learning techniques
HIGHLIGHTS who: Zahra Gharineiat and colleagues from the School of Surveying and Built Environment, Faculty of Health, Engineering and Sciences,
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Evaluation of classification in single cell atac-seq data with machine learning methods
HIGHLIGHTS who: Hongzhe Guo from the Faculty of Computing, Harbin Harbin, China have published the research work: Evaluation of classification
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Convolutional neural network face recognition method using fisher’s criterion
HIGHLIGHTS who: Fisher`s, Criterion and Wei, Wang from the College of Information Engineering, Zhengzhou University of Technology, Zhengzhou, China have