225 related articles for article (PubMed ID: 34688019)
1. Theory of deep convolutional neural networks III: Approximating radial functions.
Mao T; Shi Z; Zhou DX
Neural Netw; 2021 Dec; 144():778-790. PubMed ID: 34688019
[TBL] [Abstract][Full Text] [Related]
2. Theory of deep convolutional neural networks: Downsampling.
Zhou DX
Neural Netw; 2020 Apr; 124():319-327. PubMed ID: 32036229
[TBL] [Abstract][Full Text] [Related]
3. Theory of deep convolutional neural networks II: Spherical analysis.
Fang Z; Feng H; Huang S; Zhou DX
Neural Netw; 2020 Nov; 131():154-162. PubMed ID: 32781384
[TBL] [Abstract][Full Text] [Related]
4. Optimal approximation of piecewise smooth functions using deep ReLU neural networks.
Petersen P; Voigtlaender F
Neural Netw; 2018 Dec; 108():296-330. PubMed ID: 30245431
[TBL] [Abstract][Full Text] [Related]
5. Simultaneous approximation of a smooth function and its derivatives by deep neural networks with piecewise-polynomial activations.
Belomestny D; Naumov A; Puchkin N; Samsonov S
Neural Netw; 2023 Apr; 161():242-253. PubMed ID: 36774863
[TBL] [Abstract][Full Text] [Related]
6. A deep network construction that adapts to intrinsic dimensionality beyond the domain.
Cloninger A; Klock T
Neural Netw; 2021 Sep; 141():404-419. PubMed ID: 34146968
[TBL] [Abstract][Full Text] [Related]
7. Towards understanding theoretical advantages of complex-reaction networks.
Zhang SQ; Gao W; Zhou ZH
Neural Netw; 2022 Jul; 151():80-93. PubMed ID: 35405473
[TBL] [Abstract][Full Text] [Related]
8. Generalization analysis of deep CNNs under maximum correntropy criterion.
Zhang Y; Fang Z; Fan J
Neural Netw; 2024 Jun; 174():106226. PubMed ID: 38490117
[TBL] [Abstract][Full Text] [Related]
9. On the capacity of deep generative networks for approximating distributions.
Yang Y; Li Z; Wang Y
Neural Netw; 2022 Jan; 145():144-154. PubMed ID: 34749027
[TBL] [Abstract][Full Text] [Related]
10. A novel fused convolutional neural network for biomedical image classification.
Pang S; Du A; Orgun MA; Yu Z
Med Biol Eng Comput; 2019 Jan; 57(1):107-121. PubMed ID: 30003400
[TBL] [Abstract][Full Text] [Related]
11. Depth Selection for Deep ReLU Nets in Feature Extraction and Generalization.
Han Z; Yu S; Lin SB; Zhou DX
IEEE Trans Pattern Anal Mach Intell; 2022 Apr; 44(4):1853-1868. PubMed ID: 33079656
[TBL] [Abstract][Full Text] [Related]
12. A multimodal convolutional neuro-fuzzy network for emotion understanding of movie clips.
Nguyen TL; Kavuri S; Lee M
Neural Netw; 2019 Oct; 118():208-219. PubMed ID: 31299625
[TBL] [Abstract][Full Text] [Related]
13. Parallel ensemble learning of convolutional neural networks and local binary patterns for face recognition.
Tang J; Su Q; Su B; Fong S; Cao W; Gong X
Comput Methods Programs Biomed; 2020 Dec; 197():105622. PubMed ID: 32629293
[TBL] [Abstract][Full Text] [Related]
14. Deep ReLU neural networks in high-dimensional approximation.
Dũng D; Nguyen VK
Neural Netw; 2021 Oct; 142():619-635. PubMed ID: 34392126
[TBL] [Abstract][Full Text] [Related]
15. Learning hidden patterns from patient multivariate time series data using convolutional neural networks: A case study of healthcare cost prediction.
Morid MA; Sheng ORL; Kawamoto K; Abdelrahman S
J Biomed Inform; 2020 Nov; 111():103565. PubMed ID: 32980530
[TBL] [Abstract][Full Text] [Related]
16. Low-Rank Deep Convolutional Neural Network for Multitask Learning.
Su F; Shang HY; Wang JY
Comput Intell Neurosci; 2019; 2019():7410701. PubMed ID: 31236107
[TBL] [Abstract][Full Text] [Related]
17. Neural networks with ReLU powers need less depth.
Cabanilla KIM; Mohammad RZ; Lope JEC
Neural Netw; 2024 Apr; 172():106073. PubMed ID: 38159509
[TBL] [Abstract][Full Text] [Related]
18. Approximation bounds for convolutional neural networks in operator learning.
Franco NR; Fresca S; Manzoni A; Zunino P
Neural Netw; 2023 Apr; 161():129-141. PubMed ID: 36745938
[TBL] [Abstract][Full Text] [Related]
19. Stress detection using deep neural networks.
Li R; Liu Z
BMC Med Inform Decis Mak; 2020 Dec; 20(Suppl 11):285. PubMed ID: 33380334
[TBL] [Abstract][Full Text] [Related]
20. Joint multiple fully connected convolutional neural network with extreme learning machine for hepatocellular carcinoma nuclei grading.
Li S; Jiang H; Pang W
Comput Biol Med; 2017 May; 84():156-167. PubMed ID: 28365546
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]