


Fast 3D Convolution algorithms
This lecture overviews Fast 3D Convolution algorithms that has many applications in the fast implementation of 3D image and video filtering, 3D CNNs and motion estimation.



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.



Adversarial Machine Learning
This lecture overviews Adversarial Machine Learning that has many applications in DNN robustness and in privacy protection.



Domain Adaptation
This lecture overviews Domain Adaptation that has many applications in DNN training and adaptation.



Multilayer perceptron. Backpropagation
This lecture covers the basic concepts and architectures of Multi-Layer Perceptron (MLP), Activation functions, and Universal Approximation Theorem.



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.