Automatic Differentiation is Essential in Training Neural Networks for Solving Differential Equations
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Scientific Computing"
DOI: 10.1007/s10915-025-02965-3
Abstract: Neural network-based approaches have recently shown significant promise in solving partial differential equations (PDEs) in science and engineering, especially in scenarios featuring complex domains or incorporation of empirical data. One advantage of the neural network… read more here.
Keywords: training neural; automatic differentiation; differential equations; neural networks ... See more keywords
Self-paced Data Augmentation for Training Neural Networks
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.02.080
Abstract: Data augmentation is widely used for machine learning; however, an effective method to apply data augmentation has not been established even though it includes several factors that should be tuned carefully. One such factor is… read more here.
Keywords: augmentation training; self paced; augmentation; data augmentation ... See more keywords
Full waveform inversion as training a neural network
Sign Up to like & getrecommendations! Published in 2023 at "Physica Scripta"
DOI: 10.1088/1402-4896/accbb6
Abstract: Full waveform inversion (FWI) is usually solved as a nonlinear least-squares problem to minimize the discrepancy between the recorded signal and the synthetic data by some gradient-based optimization methods. In this paper, we investigate acoustic… read more here.
Keywords: neural network; network; training neural; full waveform ... See more keywords
Training Neural Networks on Remote Edge Devices for Unseen Class Classification
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2024.3383948
Abstract: Conventionally, training a deep neural network (DNN) involves minimizing an empirical risk over a training dataset that comprises a certain number of classes. However, for training more versatile DNNs on edge devices, the training datasets… read more here.
Keywords: remote edge; edge; edge devices; training neural ... See more keywords
Iterative Training of Neural Networks for Intra Prediction
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DOI: 10.1109/tip.2020.3038348
Abstract: This paper presents an iterative training of neural networks for intra prediction in a block-based image and video codec. First, the neural networks are trained on blocks arising from the codec partitioning of images, each… read more here.
Keywords: iterative training; networks intra; neural networks; intra prediction ... See more keywords
Terrain change monitoring from multi-temporal aerospace images using advanced training neural networks
Sign Up to like & getrecommendations! Published in 2025 at "Geodesy and Cartography"
DOI: 10.22389/0016-7126-2025-1019-5-39-46
Abstract: One of the key elements of the digital map making process is formation and updating of objects by detecting terrain changes from multi-temporal highly detailed aerospace images. At the same time, at present the main… read more here.
Keywords: training; training neural; multi temporal; change ... See more keywords