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Artificial Intelligence
Data Archiving and Networked Services (DANS)
A coding perspective on deep latent variable models
2020
In my thesis "A Coding Perspective on Deep Latent Variable Models", we discuss how statistical inference in Deep Latent Variable Models (DLVMs) relates to coding. In particular, we examine the minimum deception length (MDL) principle as a guide for statistica…
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Artificial Intelligence

Intelligence of machines

Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals.

High-profile applications of AI include advanced web search engines (e.g., Google Search); recommendation systems (used by YouTube, Amazon, and Netflix); virtual assistants (e.g., Google Assistant, Siri, and Alexa); autonomous vehicles (e.g., Waymo); generative and creative tools (e.g.

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Data Archiving and Networked Services (DANS)
A coding perspective on deep latent variable models
2020
In my thesis "A Coding Perspective on Deep Latent Variable Models", we discuss how statistical inference in Deep Latent Variable Models (DLVMs) relates to coding. In particular, we examine the minimum deception length (MDL) principle as a guide for statistical inference. In this context, we explore its relation to Bayesian inference. We shall see that despite both leading to similar algorithms, the MDL principle allows us to make no assumption about the data generating process. We merely restrict ourselves to find…
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