1. Hinton, G.E., Srivastava, N., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.R.: Improving neural networks by preventing co-adaptation of feature detectors, vol. 1 (2012)
2. Wu, J.-W., Chang, K.-Y., Fu, L.-C.: Adaptive under-sampling deep neural network for rapid and reliable image recovery in confocal laser scanning microscope measurements. IEEE Trans. Instrum. Meas. 71, 1–9 (2022). OCLC: 9359636331
3. Yingbin, B., Erkun, Y., Bo, H.: Understanding and Improving Early Stopping for Learning with Noisy Labels. OCLC: 1269561528 (2021)
4. Senen-Cerda, A., Sanders, J.: Almost sure convergence of dropout algorithms for neural networks. OCLC: 1144830913 (2020)
5. Liang, X., Wu, L., Li, J., Wang, Y., Meng, Q.: R-Drop: Regularized Dropout for Neural Networks. OCLC: 1269560920 (2021)