Matches in SemOpenAlex for { <https://semopenalex.org/work/W4384644622> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W4384644622 abstract "Neural network-based variational Monte Carlo (NN-VMC) has emerged as a promising cutting-edge technique of ab initio quantum chemistry. However, the high computational cost of existing approaches hinders their applications in realistic chemistry problems. Here, we report the development of a new NN-VMC method that achieves a remarkable speed-up by more than one order of magnitude, thereby greatly extending the applicability of NN-VMC to larger systems. Our key design is a novel computational framework named Forward Laplacian, which computes the Laplacian associated with neural networks, the bottleneck of NN-VMC, through an efficient forward propagation process. We then demonstrate that Forward Laplacian is not only versatile but also facilitates more developments of acceleration methods across various aspects, including optimization for sparse derivative matrix and efficient neural network design. Empirically, our approach enables NN-VMC to investigate a broader range of atoms, molecules and chemical reactions for the first time, providing valuable references to other ab initio methods. The results demonstrate a great potential in applying deep learning methods to solve general quantum mechanical problems." @default.
- W4384644622 created "2023-07-19" @default.
- W4384644622 creator A5029283570 @default.
- W4384644622 creator A5036614045 @default.
- W4384644622 creator A5040376632 @default.
- W4384644622 creator A5040517373 @default.
- W4384644622 creator A5055723755 @default.
- W4384644622 creator A5057316665 @default.
- W4384644622 creator A5064404279 @default.
- W4384644622 creator A5071536148 @default.
- W4384644622 creator A5074740984 @default.
- W4384644622 creator A5077279992 @default.
- W4384644622 creator A5082941252 @default.
- W4384644622 date "2023-07-16" @default.
- W4384644622 modified "2023-10-16" @default.
- W4384644622 title "Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo" @default.
- W4384644622 doi "https://doi.org/10.48550/arxiv.2307.08214" @default.
- W4384644622 hasPublicationYear "2023" @default.
- W4384644622 type Work @default.
- W4384644622 citedByCount "0" @default.
- W4384644622 crossrefType "posted-content" @default.
- W4384644622 hasAuthorship W4384644622A5029283570 @default.
- W4384644622 hasAuthorship W4384644622A5036614045 @default.
- W4384644622 hasAuthorship W4384644622A5040376632 @default.
- W4384644622 hasAuthorship W4384644622A5040517373 @default.
- W4384644622 hasAuthorship W4384644622A5055723755 @default.
- W4384644622 hasAuthorship W4384644622A5057316665 @default.
- W4384644622 hasAuthorship W4384644622A5064404279 @default.
- W4384644622 hasAuthorship W4384644622A5071536148 @default.
- W4384644622 hasAuthorship W4384644622A5074740984 @default.
- W4384644622 hasAuthorship W4384644622A5077279992 @default.
- W4384644622 hasAuthorship W4384644622A5082941252 @default.
- W4384644622 hasBestOaLocation W43846446221 @default.
- W4384644622 hasConcept C105795698 @default.
- W4384644622 hasConcept C115178988 @default.
- W4384644622 hasConcept C121332964 @default.
- W4384644622 hasConcept C132525143 @default.
- W4384644622 hasConcept C149635348 @default.
- W4384644622 hasConcept C154945302 @default.
- W4384644622 hasConcept C16016025 @default.
- W4384644622 hasConcept C165700671 @default.
- W4384644622 hasConcept C178790620 @default.
- W4384644622 hasConcept C185592680 @default.
- W4384644622 hasConcept C19499675 @default.
- W4384644622 hasConcept C26517878 @default.
- W4384644622 hasConcept C2780513914 @default.
- W4384644622 hasConcept C2781442258 @default.
- W4384644622 hasConcept C33923547 @default.
- W4384644622 hasConcept C38652104 @default.
- W4384644622 hasConcept C41008148 @default.
- W4384644622 hasConcept C50644808 @default.
- W4384644622 hasConcept C62520636 @default.
- W4384644622 hasConcept C80444323 @default.
- W4384644622 hasConcept C84114770 @default.
- W4384644622 hasConceptScore W4384644622C105795698 @default.
- W4384644622 hasConceptScore W4384644622C115178988 @default.
- W4384644622 hasConceptScore W4384644622C121332964 @default.
- W4384644622 hasConceptScore W4384644622C132525143 @default.
- W4384644622 hasConceptScore W4384644622C149635348 @default.
- W4384644622 hasConceptScore W4384644622C154945302 @default.
- W4384644622 hasConceptScore W4384644622C16016025 @default.
- W4384644622 hasConceptScore W4384644622C165700671 @default.
- W4384644622 hasConceptScore W4384644622C178790620 @default.
- W4384644622 hasConceptScore W4384644622C185592680 @default.
- W4384644622 hasConceptScore W4384644622C19499675 @default.
- W4384644622 hasConceptScore W4384644622C26517878 @default.
- W4384644622 hasConceptScore W4384644622C2780513914 @default.
- W4384644622 hasConceptScore W4384644622C2781442258 @default.
- W4384644622 hasConceptScore W4384644622C33923547 @default.
- W4384644622 hasConceptScore W4384644622C38652104 @default.
- W4384644622 hasConceptScore W4384644622C41008148 @default.
- W4384644622 hasConceptScore W4384644622C50644808 @default.
- W4384644622 hasConceptScore W4384644622C62520636 @default.
- W4384644622 hasConceptScore W4384644622C80444323 @default.
- W4384644622 hasConceptScore W4384644622C84114770 @default.
- W4384644622 hasLocation W43846446221 @default.
- W4384644622 hasOpenAccess W4384644622 @default.
- W4384644622 hasPrimaryLocation W43846446221 @default.
- W4384644622 hasRelatedWork W1945545427 @default.
- W4384644622 hasRelatedWork W1983196284 @default.
- W4384644622 hasRelatedWork W1987642295 @default.
- W4384644622 hasRelatedWork W2015141447 @default.
- W4384644622 hasRelatedWork W2037355886 @default.
- W4384644622 hasRelatedWork W2082887956 @default.
- W4384644622 hasRelatedWork W2086821297 @default.
- W4384644622 hasRelatedWork W2417221773 @default.
- W4384644622 hasRelatedWork W4239486554 @default.
- W4384644622 hasRelatedWork W4295795203 @default.
- W4384644622 isParatext "false" @default.
- W4384644622 isRetracted "false" @default.
- W4384644622 workType "article" @default.