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Machine Learning for Quantum Applications - Lecture 3

Offered By: ICTP Condensed Matter and Statistical Physics via YouTube

Tags

Machine Learning Courses Artificial Intelligence Courses Data Science Courses Neural Networks Courses Quantum Computing Courses Quantum Information Courses Quantum Physics Courses Quantum Error Correction Courses

Course Description

Overview

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Explore advanced concepts in machine learning for quantum applications in this comprehensive lecture by Eliska Greplova from Delft University of Technology. Delve into cutting-edge techniques and methodologies that bridge the gap between machine learning and quantum physics. Gain insights into how these powerful tools can be applied to solve complex problems in quantum systems and enhance our understanding of quantum phenomena. Discover the latest developments in this rapidly evolving field and learn how machine learning algorithms can be leveraged to optimize quantum experiments, analyze quantum data, and accelerate quantum research. Enhance your knowledge of both machine learning and quantum physics, and understand their synergistic potential in advancing scientific discovery and technological innovation.

Syllabus

Machine learning for quantum applications 3


Taught by

ICTP Condensed Matter and Statistical Physics

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