ADR Awareness Centre

Procedural content generation (PCG) is an increasingly important area of technology within modern human-computer interaction (HCI) design.

This lecture will cover the basic concepts of Artificial Neural Networks (ANNs): Biological neural models, Perceptron, Activation functions, Loss types, Steepest Gradient Descent, On-line Perceptron training, Batch Perceptron training.

This lecture overviews Deep Autoencoders that has many applications in image denoising, classification, generation and in object pose estimation.

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.

In contrast with random uniform instances, industrial SAT instances of large size are solvable today by state-of-the-art algorithms.

The adaptive processing of graph data is a long-standing research topic that has been lately consolidated as a theme of major interest in the deep learning community.