Event Videos
George Booth: Gaussian Process States: Explicitly Data-driven wave functions
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Giacomo Torlai: Quantum process tomography with unsupervised learning and tensor networks
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Robert Huang: Predicting Many Properties of a Quantum System from Very Few Measurements
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Attila Szabó: Neural network wave functions and the sign problem
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Christian Mendl: Real time evolution with neural-network quantum states by approximating the implicit midpoint method
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Yusuke Nomura: Application of machine learning beyond benchmarks reveals Dirac-type nodal spin liquid in the J1-J2 Heisenberg model
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James Spencer: Ab-Initio Solution of the Many-Electron Schrödinger Equation with Deep Neural Network
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Roberto Car: Molecular simulation with the deep potential method
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Frank Noé: PauliNet – deep learning the electronic Schrödinger equation
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