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pro vyhledávání: '"Gao Tianxiang"'
Neural networks with wide layers have attracted significant attention due to their equivalence to Gaussian processes, enabling perfect fitting of training data while maintaining generalization performance, known as benign overfitting. However, existi
Externí odkaz:
http://arxiv.org/abs/2310.10767
Publikováno v:
Aquatic Living Resources, Vol 32, p 8 (2019)
Tissue samples from 84 Pampus chinensis individuals were collected from four geographic regions within the Indo–Pacific Ocean and analyzed using mitochondrial and nuclear DNA markers. Distinct genetic heterogeneity was found for both types of marke
Externí odkaz:
https://doaj.org/article/509d0cc7666649d6b9335e0573ce19e6
Publikováno v:
Aquatic Living Resources, Vol 32, p 18 (2019)
In order to study the genetic diversity of Thamnaconus modestus, a species of great commercial importance in Southeast Asia, the 5′-end hypervariable regions (423 bp) of the mitochondrial control region of T. modestus in nine geographical populatio
Externí odkaz:
https://doaj.org/article/9be1cb0c67314ca7bafac8522c69a645
Publikováno v:
Aquatic Living Resources, Vol 31, p 32 (2018)
Platycephalus cultellatus Richardson, 1846 was originally found and named in its type locality, Canton, Guangdong Province, China. However, this species was very rare in the coastal waters of China. Except that Qin et al. simply mentioned the origina
Externí odkaz:
https://doaj.org/article/0ce2d59d292c4605bdb54bd02dbace37
Autor:
Gao, Tianxiang, Gao, Hongyang
Implicit neural networks have become increasingly attractive in the machine learning community since they can achieve competitive performance but use much less computational resources. Recently, a line of theoretical works established the global conv
Externí odkaz:
http://arxiv.org/abs/2209.15562
Autor:
Gao, Tianxiang, Gao, Hongyang
Implicit deep learning has recently become popular in the machine learning community since these implicit models can achieve competitive performance with state-of-the-art deep networks while using significantly less memory and computational resources
Externí odkaz:
http://arxiv.org/abs/2205.07463
Publikováno v:
In Pattern Recognition Letters September 2024 185:59-65
Publikováno v:
In Journal of Invertebrate Pathology September 2024 206
Publikováno v:
In International Communications in Heat and Mass Transfer December 2024 159 Part B