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by
Li, Zhong, author.
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Physics-based Dynamic Reconstruction of Deformable Objects / Li, Zhong, author.
by
Sheldon, Forrest C., author.
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University of California, San Diego. Physics. degree granting institution.
by
Figgatt, Caroline Margaret, author. (orcid)0000-0001-8460-4175
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University of Maryland, College Park. Physics. degree granting institution.
by
Pedersen, Keith, author.
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Illinois Institute of Technology. Physics. degree granting institution.
by
Hu, Wenjian, author.
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University of California, Davis. Physics. degree granting institution.
by
Dodds, Eric, author.
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University of California, Berkeley. Physics. degree granting institution.
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Almada, Demetrius J., author.
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San Jose State University. Physics. degree granting institution.
by
Pant, Mihir, author.
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Quantum physics.
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Metzgar, Jonathan Brian, author.
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Physics.
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Monaco, Benjamin, author.
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Computational physics.
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Chen, Desai, author.
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Physics.
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Kostakis, Dimitrios, author.
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Statistical physics.
by
Crockatt, Michael M., author.
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Computational physics.
by
Li, Mingda, author. (orcid)0000-0002-0494-3853
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accurate, efficient, and generic device compact modeling algorithm: physics-inspired neural network (Pi-NN).
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Ulu, Nurcan Gecer, author.
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support design by high-level functional prescriptions, a physics based shape optimization method for
by
Liu, Tiantian, author.
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We propose a new method for physics-based simulation supporting many different types of
by
Jadhav, Shrikant Shridhar, author.
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-informatics, neuroinformatics, physics, computer vision, etc. where significant processing capability is required.
by
Roychowdhury, Anirban, author.
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In the third section, we use concepts from statistical physics to develop a robust Monte Carlo

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