Displaying 105 resources
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Graph Convolutional Networks
This lecture overviews Graph Convolutional Networks (GCN) that have many applications in Deep Learning, Signal and Video Analysis, Network Theory, Web Science and Social Media Analytics. It covers the following topics in detail: Graph Convolutions.
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Convolutional Neural Networks Lecture
Convolutional Neural Networks form the backbone of current AI revolution and are used in a multitude of classification and regression problems. This lecture overviews the transition from multilayer perceptrons to deep architectures.
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Multilayer perceptron. Backpropagation
This lecture covers the basic concepts and architectures of Multi-Layer Perceptron (MLP), Activation functions, and Universal Approximation Theorem.
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Attention and Transformers Networks
In this lecture, the limitations of Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs) in effectively processing sequences are emphasized.
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Adversarial Machine Learning
This lecture overviews Adversarial Machine Learning that has many applications in DNN robustness and in privacy protection.
Certification
Online Course
Tutorial/How To/Guides
Graph Neural Networks
This lecture overviews Graph Neural Networks that has many applications in Deep Learning, Signal and Video Analysis, Network Theory, Web Science and Social Media Analytics. It covers the following topics in detail: Introduction to Graphs.