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Explore advanced machine learning techniques applied to cosmological research in this comprehensive lecture from the V Joint ICTP-Trieste/ICTP-SAIFR School on Cosmology. Learn from Francisco Antonio Villaescusa Navarro of the Simons Foundation and Princeton University as he delves into the second installment of his specialized course on machine learning methods for cosmology. Discover how artificial intelligence and computational techniques are revolutionizing our understanding of the universe, from analyzing large-scale structure formation to extracting cosmological parameters from observational data. Gain insights into cutting-edge methodologies that bridge the gap between theoretical cosmology and practical data analysis, essential for modern astrophysics research. This lecture forms part of an intensive two-week international school program designed to advance knowledge in contemporary cosmological studies through interdisciplinary approaches combining physics, mathematics, and computer science.
