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\nRecorded\n20 February 2018\nin Lausanne, Vaud, Switzerland\n<\/p>\n
\nEvent:<\/b>\nMARVEL NCCR<\/a>\n- MARVEL Distinguished Lectures, Seminars and Tutorials - 2015 onwards \n<\/p>\n This lecture is designed to be accessible to a wide variety of backgrounds.<\/p>\n\n In the first part, I will briefly review density functional theory and why it is important to many branches of modern physical science. I will also review machine learning and its recent applications to molecules and materials.<\/p>\n\n In the second half, I will show how, in collaboration with computer scientists at TU Berlin, we have used a specific type of machine-learning, called kernel ridge regression, to find more accurate and powerful approximate density functionals than any made by humans.<\/p>\n\n For more background, see here<\/a>.<\/p>\n\n<\/div>\n Watched 1613 times.<\/p>\n<\/i> Watch<\/a>\n<\/div>\n<\/div>\n<\/div>\n');
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Abstract<\/h4>\n