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Full-Text Articles in Physical Chemistry
Automated Code Engine For Tensor Hypercontraction: Derivation, Optimization And Implementation Of Rank-Reduced Coupled Cluster Theories, Yao Zhao
Dissertations, Theses, and Capstone Projects
The ultimate goal of electronic structure theory is solving the electronic Schr¨odinger Equation. However, even accurate approximations of solving Schr¨odinger Equation, such as high order coupled cluster theories, require computational efforts that are too demanding to be applied on large chemical systems. This thesis tackles the problem of curse of dimensionality: how to reduce the time complexity of high-accuracy coupled cluster methods in order to accelerate computations of molecular energy. On one hand, we believe that low-rank approximation (i.e. Tensor HyperContraction) of high-order tensors appearing in coupled cluster theory is a promising way to achieve rank-reduced coupled cluster theory. On …
Awegnn: Auto-Parametrized Weighted Element-Specific Graph Neural Networks For Molecules., Timothy Szocinski, Duc Duy Nguyen, Guo-Wei Wei
Awegnn: Auto-Parametrized Weighted Element-Specific Graph Neural Networks For Molecules., Timothy Szocinski, Duc Duy Nguyen, Guo-Wei Wei
Mathematics Faculty Publications
While automated feature extraction has had tremendous success in many deep learning algorithms for image analysis and natural language processing, it does not work well for data involving complex internal structures, such as molecules. Data representations via advanced mathematics, including algebraic topology, differential geometry, and graph theory, have demonstrated superiority in a variety of biomolecular applications, however, their performance is often dependent on manual parametrization. This work introduces the auto-parametrized weighted element-specific graph neural network, dubbed AweGNN, to overcome the obstacle of this tedious parametrization process while also being a suitable technique for automated feature extraction on these internally complex …