Displaying 115 resources
Image and Video Generation: A deep Learning Approach
This resource corresponds to 7th video from the AI Excellence Lecture Series.
This video explores the fascinating realm of image and video generation through the lens of deep learning.
Generative Adversarial Networks
This lecture overviews Generative Adversarial Networks that have many applications in Media Production.
Introduction to Statistics
This lecture provides an Introduction to Statistics that has many applications in Data Analytics, Machine Learning and Signal Analysis. It covers the following topics in detail: Random Variables. Data Types. Data Sampling.
Super Resolution
This lecture overviews Super Resolution that has many applications in digital imaging, display and printing.
The power of cooperation in networks of learning agents
We study the power of cooperation in a network of communicating agents that solve a learning task. Agents use an underlying communication network to get information about what the other agents know.
Orthogonal Signal Transforms. Fourier Series
This lecture overviews Orthogonal Signal Transforms. Fourier Series that has many applications in signal processing, analysis and compression.
Robust Statistics
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.
Robot and Drone Swarms
This lecture overviews Robot and Drone Swarms that has many applications in autonomous systems: cars/drones.
Graph Convolutional Networks
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.
Fast 2D Convolutions Algorithms
This lecture will overview 2D linear and cyclic convolution. Then it will present their fast execution through FFTs, resulting in algorithms having computational complexity of the order O(N^2log2N).
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.