ADR Awareness Centre

This lecture overviews Neural Image Compression that has many applications in image storage and communications.

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.

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

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.