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02 - David Ceperley - Introduction to Stochastic Methods
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Talks given at the QMC Summer Training, June 6-10, 2016 at the National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign. The QMC training is funded by the Predictive Theory and Modeling for Materials and Chemical Science program of the Basic Energy Sciences, U.S. Department of Energy. The 2016 training was also supported by Argonne Leadership Computing Facility, the National Center for Supercomputing Applications, the Frederick Seitz Materials Research Laboratory, and the Physics Department, University of Illinois.
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02 - David Ceperley - Introduction to Stochastic Methods
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David Ceperley - Path integral theory of exchange in quantum crystals
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Hydrogen under Extreme Conditions -- David Ceperley, University of Illinois at Urbana-Champaign
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03 - David Ceperley - Variational Monte Carlo
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MagLab Theory Winter School 2017: David Ceperley - Ab-initio Quantum Monte-Carlo (QMC) Methods
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Quantum Machine Learning - 19 - Sampling a Thermal State
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Quantum Monte Carlo in Finance: #1 Killer Application?
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CAS Symposium SessionOne April 20, 2015
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Mr. Richard Goodall gives a special performance
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A multi-agent quantum Monte Carlo model for charge transport: Application to organic field-effect...
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MC simulations: 1.0 Welcome
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Maxim Raginsky: The limits of control: An information-theoretic viewpoint
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Discover Saturn's Hidden Depths: Metallic Hydrogen & Solid Core
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Andreas Grüneis: Reaching Chemical Accuracy in ab initio Simulations of Complex Materials
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PH4209 : L28 - Path Integral for Gauge Theory
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Diagrammatic Monte Carlo for real-time propagation
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Quantum Monte Carlo Top # 5 Facts
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Anthony Maggs: Irreversible Monte Carlo methods for particle simulations
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Relativistic Monte Carlo
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Matt and Kim Daylight acoustic cover
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AQC 2016 - Avoiding Negative Sign Problem in Simulation of Quantum Annealilng
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Quantum Monte Carlo in Julia | Rafał Pracht | JuliaCon 2023
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U3pt2 Models of H Atom Simulation
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Time-dependent variational Monte Carlo Top #6 Facts
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