Graph Neural Networks
Graph Neural Networks (GNNs) are a versatile form of neural networks that encompass various network architectures like NNs, CNNs, and RNNs, as well as unsupervised learning models such as RBM and DBNs. They find applications in diverse fields such as object detection, machine translation, and drug d
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Recent Advances in RNN and CNN Models: CS886 Lecture Highlights
Explore the fundamentals of recurrent neural networks (RNNs) and convolutional neural networks (CNNs) in the context of downstream applications. Delve into LSTM, GRU, and RNN variants, alongside CNN architectures like ConvNext, ResNet, and more. Understand the mathematical formulations of RNNs and c
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Weekly Activities and Research Updates in Machine Learning - April 18, 2023
Adri Priadana's weekly report details recent activities like courses on machine learning, doctoral thesis research, and face recognition experiments using PyTorch. Updates on FasterNet Block, Split-based Inception Block, ResNet architecture modifications for improved face recognition accuracy are in
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