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Explore advanced machine learning techniques applied to cosmological research in this 74-minute 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 presents the third installment of his comprehensive series 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 data to modeling cosmic phenomena. Gain insights into cutting-edge approaches that combine statistical learning with astrophysical observations to extract meaningful information about dark matter, dark energy, and the fundamental parameters governing our cosmos. This advanced-level presentation is part of an intensive two-week international school program designed for researchers and graduate students working at the intersection of cosmology and computational methods.
