Public Research Seminar by Advanced Materials (AMAT) Thrust, HKUST(GZ) - Generative AI for it
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Besides bits, generative AI holds immense potential in generating and designing “it” — matter at the atomic scale. Specifically, due to the inherent connection between generative models and statistical physics, they offer a unique advantage in optimizing Nature’s cost function, the variational free energy, thereby providing new possibilities for solving difficult problems in quantum many-body physics. In this talk, I will discuss applications of generative models at the atomic level with concrete examples. I hope these examples also highlight intriguing connections across the field, to name a few: language model & chemical intuitions, reinforcement learning & variational inference, flow model & adiabatic continuity.
Lei Wang obtained his Bachelor degree from Nanjing University in 2006 and a PhD from the Institute of Physics, Chinese Academy of Sciences in 2011. He did postdoctoral research on computational quantum physics at ETH Zurich in the next few years. Lei Wang joined the Institute of Physics in 2016. His research interest is at the cross-section of deep learning and quantum many-body computation.