


Image Sampling
This lecture overviews spatial image frequency content and image sampling. Rectangular and hexagonal sampling grids are presented. Sampled image frequency content is analyzed and a 2D version of Shannon theorem is presented.


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



Stereotypes in Language & Computational Language Models
Combined knowledge from linguistics, psychology, and natural language processing.



Understanding and mitigating bias in AI automated systems
“The AI community has been focusing on developing fixes for harmful bias and discrimination, through so-called ‘debiasing algorithms’ that either try to fix data for known or expected biases, or constrain the outcomes of a given predictive model t



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



Artificial Neural Networks. Perceptron
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.