ADR Awareness Centre

This lecture overviews Transfer Learning (TL) that has many applications in DNN training and adaptation, Image Understanding, Text Mining, Activity Recognition, Bioinformatics, Transportation.

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.

This lecture overviews Data Clustering  that has many applications in e.g., facial image clustering, signal/image clustering, concept creation.  It covers the following topics in detail: Clustering Definitions.

This lecture overviews Robust Statistics that has many applications in Data Analytics and Digital Signal Processing and Analysis. It covers the following topics in detail: Outliers.

Generative Adversarial Networks (GANs) are part of the cutting edge in recent machine learning research.

The survey provides a comprehensive overview of deep learning methods for geometric data (point clouds, voxels, network graphs etc.). The relevant knowledge and theoretical background of geometric deep learning is presented first.