Large language models have become ubiquitous. This lecture introduces to language modelling and large language models. We will discover what they are, where they come from and the primary motivations behind their design. We then provide an overview of the properties of these models when trained at the current scale of very large language models.
If time remains, we introduce the problematic...
Very large amounts of high-dimensional data are now omnipresent
(ranging from traditional multidimensional data to time series and deep
embeddings), and the performance requirements (i.e., response-time and
accuracy) of a variety of applications that need to process and analyze
these data have become very stringent and demanding. In the past years, high-dimensional similarity search has...
Anomaly detection is an important problem in data analytics with applications in many domains. In recent years, there has been an increasing interest in anomaly detection tasks applied to time series. In this talk, we take a holistic view of anomaly detection in time series, starting from the core definitions and taxonomies related to time series and anomaly types, to an extensive description...
Particle physics deals with gigantic machines, large quantities of experimental data and computer simulations, complex and lengthy theoretical calculations. It is the perfect playground to take advantage of machine learning algorithms. After a short introduction to high energy physics, this lecture will show how one can speed up steps like event generation or detector simulation, better...
