Neural Networks and Deep Learning

By Charu C. Aggarwal. Cambridge International Law Journal, 2018

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Deepfake Video Detection Using Convolutional Vision Transformer (2021, background): “GANs are generative models that are designed to create generative models of data from samples [3, 18].”
Artificial Intelligence and Marketing: Pitfalls and Opportunities (2020, background): “For overall introductory references to deep learning, we also refer to Goodfellow, Bengio, and Courville (2016), Kelleher (2019), and Aggarwal (2018).”
Federated learning enables big data for rare cancer boundary detection (2022, methodology): “These speciﬁc 6 out-of-sample sites (Site IDs: 8, 11, 19, 20, 21, 43) were allocated based on their availability, i.e., they have indicated an expected delayed participation rendering them optimal for model generalizability validation.”
ADBench: Anomaly Detection Benchmark (2022, background): “Recent machine learning books [4, 54] and scikit-learn [133] may serve as good sources of supervised ML methods.”
The Creation and Detection of Deepfakes (2020, methodology): “2 Loss Functions In order to update the weights with an optimization algorithm, such as GD, the loss function must be differentiable [7].”