Добірка наукової літератури з теми "Density embedding"
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Статті в журналах з теми "Density embedding"
Knizia, Gerald, and Garnet Kin-Lic Chan. "Density Matrix Embedding: A Strong-Coupling Quantum Embedding Theory." Journal of Chemical Theory and Computation 9, no. 3 (February 21, 2013): 1428–32. http://dx.doi.org/10.1021/ct301044e.
Повний текст джерелаYe, Hong-Zhou, Matthew Welborn, Nathan D. Ricke, and Troy Van Voorhis. "Incremental embedding: A density matrix embedding scheme for molecules." Journal of Chemical Physics 149, no. 19 (November 21, 2018): 194108. http://dx.doi.org/10.1063/1.5053992.
Повний текст джерелаDžamonja, Mirna. "Isomorphic Universality and the Number of Pairwise Nonisomorphic Models in the Class of Banach Spaces." Abstract and Applied Analysis 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/184071.
Повний текст джерелаArtiukhin, Denis G., Christoph R. Jacob, and Johannes Neugebauer. "Excitation energies from frozen-density embedding with accurate embedding potentials." Journal of Chemical Physics 142, no. 23 (June 21, 2015): 234101. http://dx.doi.org/10.1063/1.4922429.
Повний текст джерелаLaricchia, S., E. Fabiano, and F. Della Sala. "Frozen density embedding with hybrid functionals." Journal of Chemical Physics 133, no. 16 (October 28, 2010): 164111. http://dx.doi.org/10.1063/1.3494537.
Повний текст джерелаCulpitt, Tanner, Kurt R. Brorsen, Michael V. Pak, and Sharon Hammes-Schiffer. "Multicomponent density functional theory embedding formulation." Journal of Chemical Physics 145, no. 4 (July 28, 2016): 044106. http://dx.doi.org/10.1063/1.4958952.
Повний текст джерелаHršak, Dalibor, Jógvan Magnus Haugaard Olsen, and Jacob Kongsted. "Polarizable Density Embedding Coupled Cluster Method." Journal of Chemical Theory and Computation 14, no. 3 (February 14, 2018): 1351–60. http://dx.doi.org/10.1021/acs.jctc.7b01153.
Повний текст джерелаHedegård, Erik D., and Markus Reiher. "Polarizable Embedding Density Matrix Renormalization Group." Journal of Chemical Theory and Computation 12, no. 9 (September 2016): 4242–53. http://dx.doi.org/10.1021/acs.jctc.6b00476.
Повний текст джерелаIannuzzi, Marcella, Barbara Kirchner, and Jürg Hutter. "Density functional embedding for molecular systems." Chemical Physics Letters 421, no. 1-3 (April 2006): 16–20. http://dx.doi.org/10.1016/j.cplett.2005.08.155.
Повний текст джерелаNiffenegger, K., Y. Oueis, J. Nafziger, and A. Wasserman. "Density embedding with constrained chemical potential." Molecular Physics 117, no. 15-16 (May 21, 2019): 2188–94. http://dx.doi.org/10.1080/00268976.2019.1618939.
Повний текст джерелаДисертації з теми "Density embedding"
Wang, Haolei. "Using density-based clustering to improve skeleton embedding in the Pinocchio automatic rigging system." Thesis, Kansas State University, 2012. http://hdl.handle.net/2097/15102.
Повний текст джерелаDepartment of Computing and Information Sciences
William H. Hsu
Automatic rigging is a targeting approach that takes a 3-D character mesh and an adapted skeleton and automatically embeds it into the mesh. Automating the embedding step provides a savings over traditional character rigging approaches, which require manual guidance, at the cost of occasional errors in recognizing parts of the mesh and aligning bones of the skeleton with it. In this thesis, I examine the problem of reducing such errors in an auto-rigging system and apply a density-based clustering algorithm to correct errors in a particular system, Pinocchio (Baran & Popovic, 2007). I show how the density-based clustering algorithm DBSCAN (Ester et al., 1996) is able to filter out some impossible vertices to correct errors at character extremities (hair, hands, and feet) and those resulting from clothing that hides extremities such as legs.
Reinhard, Teresa Elisabeth [Verfasser], and Angel [Akademischer Betreuer] Rubio. "Density Matrix Embedding Theory : Foundations, Applications and Connection to Functional Theories / Teresa Elisabeth Reinhard ; Betreuer: Angel Rubio." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2019. http://d-nb.info/1186891157/34.
Повний текст джерелаHeuser, Johannes [Verfasser], and S. [Akademischer Betreuer] Höfener. "Analytische Kerngradienten für Frozen-Density Embedding-RICC2 zur Untersuchung angeregter Zustände komplexer Systeme / Johannes Heuser ; Betreuer: S. Höfener." Karlsruhe : KIT-Bibliothek, 2018. http://d-nb.info/1168325676/34.
Повний текст джерелаMordovina, Uliana [Verfasser], and Angel [Akademischer Betreuer] Rubio. "Novel Approaches in Quantum Chemistry : Self-Consistent Density-Functional Embedding and Polaritonic Coupled-Cluster Theory / Uliana Mordovina ; Betreuer: Angel Rubio." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2020. http://d-nb.info/1210647176/34.
Повний текст джерелаSenjean, Bruno. "Development of new embedding techniques for strongly correlated electrons : from in-principle-exact formulations to practical approximations." Thesis, Strasbourg, 2018. http://www.theses.fr/2018STRAF035/document.
Повний текст джерелаThe thesis deals with the development and implementation of new methods for the description of strong electron correlation effects in molecules and solids. After introducing the state of the art in quantum chemistry and in condensed matter physics, a new hybrid method so-called ``site-occupation embedding theory'' (SOET) is presented and is based on the merging of wavefunction theory and density functional theory (DFT). Different formulations of this theory are described and applied to the one-dimensional Hubbard model. In addition, a novel ensemble density functional theory approach has been derived to extract the fundamental gap exactly. In the latter approach, the infamous derivative discontinuity is reformulated as a derivative of a weight-dependent exchange-correlation functional. Finally, a quantum chemical extension of SOET is proposed and based on a seniority-zero wavefunction, completed by a functional of the density matrix and expressed in the natural orbital basis
Werner, Martin. "Low-Scaling Local and Fragment Self-Consistent Field Potentials in Molecular Systems." Doctoral thesis, Niedersächsische Staats- und Universitätsbibliothek Göttingen, 2017. http://hdl.handle.net/11858/00-1735-0000-002E-E311-5.
Повний текст джерелаHayashi, Kazuki. "Reinforcement Learning for Optimal Design of Skeletal Structures." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/263614.
Повний текст джерелаPritzsche, Marc. "Dichtefunktional-Rechnungen zu selektiven Oxidationen von Propan und Methanol mittels Vanadiumoxidkatalysatoren auf Siliziumdioxidträgern." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2008. http://dx.doi.org/10.18452/15832.
Повний текст джерелаIn this work cluster models and models for QM/MM-embedding for supported vanadia catalysts on silica were studied with help of DFT-calculations. The structures, vibrations and stability towards water and oxygen under reaction conditions were examined. Furthermore the reactivities towards the oxidative dehydrogenation (ODH) of n-propane to n-propene and the oxidation of methanol to formaldehyde were tested. For the embedding an adapted shell-model-potential was employed. Regarding the vibrations it was shown that the influence of the embedding lies mostly in the coupling of vibrations and not in their frequencies. The local structure surrounding the vanadium atom has only minor influence. The stability calculations have shown that the tested model systems exist under reaction conditions while hydroxylated species do not exist. When studying the reactivity of the two reactions always the same mechanism is found for cluster and embedded calculations. The benefit of the embedded calculations is the possibility to vary the local structure surrounding the active center. For the ODH of propane the local structure has only small impact on reaction energies because the reaction takes mainly place at the vanadyl oxygen. The transition state of the rate determining step nevertheless is energetically higher in the embedded calculations due to steric hindrance caused by the hydroxyl groups of the surface. The impact of local structure is more important for the oxidation of methanol since in this case vanadyl oxygen and bridging oxygens to the support are involved in the reaction. For both reactions an influence on reaction energies of the vanadia loading is found. With more loading the reactions becomes more exothermic.
Goodpaster, Jason Daniel. "Density Functional Theory Embedding for Correlated Wavefunctions." Thesis, 2014. https://thesis.library.caltech.edu/8451/2/thesis_goodpaster.pdf.
Повний текст джерелаMethods that exploit the intrinsic locality of molecular interactions show significant promise in making tractable the electronic structure calculation of large-scale systems. In particular, embedded density functional theory (e-DFT) offers a formally exact approach to electronic structure calculations in which the interactions between subsystems are evaluated in terms of their electronic density. In the following dissertation, methodological advances of embedded density functional theory are described, numerically tested, and applied to real chemical systems.
First, we describe an e-DFT protocol in which the non-additive kinetic energy component of the embedding potential is treated exactly. Then, we present a general implementation of the exact calculation of the non-additive kinetic potential (NAKP) and apply it to molecular systems. We demonstrate that the implementation using the exact NAKP is in excellent agreement with reference Kohn-Sham calculations, whereas the approximate functionals lead to qualitative failures in the calculated energies and equilibrium structures.
Next, we introduce density-embedding techniques to enable the accurate and stable calculation of correlated wavefunction (CW) in complex environments. Embedding potentials calculated using e-DFT introduce the effect of the environment on a subsystem for CW calculations (WFT-in-DFT). We demonstrate that WFT-in-DFT calculations are in good agreement with CW calculations performed on the full complex.
We significantly improve the numerics of the algorithm by enforcing orthogonality between subsystems by introduction of a projection operator. Utilizing the projection-based embedding scheme, we rigorously analyze the sources of error in quantum embedding calculations in which an active subsystem is treated using CWs, and the remainder using density functional theory. We show that the embedding potential felt by the electrons in the active subsystem makes only a small contribution to the error of the method, whereas the error in the nonadditive exchange-correlation energy dominates. We develop an algorithm which corrects this term and demonstrate the accuracy of this corrected embedding scheme.
Chen, Kai-Ren, and 陳楷壬. "A study of an efficient embedding algorithm for low-density generator matrix embedding." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/33405377748998150451.
Повний текст джерела國立勤益科技大學
資訊工程系
102
This study investigated the belief propagation(Bias Propagation, BiP) algorithm proposed by Fridrich. Low-density parity-check [9] (LDPC) coding is a matrix embedding method. If a parity-check matrix with LDPC codes serves as a generator matrix and the BiP [1] algorithm is derived from this coding framework, the embedding efficiency and the computation speed of the BiP algorithm are superior to that of conventional matrix algorithms. In this study, MATLAB was used to simulate experimental data obtained from various algorithms. The results indicated that the embedding efficiency of the BiP algorithm surpassed that of other previously investigated algorithms. For the BiP algorithm, four parameters (i.e., gamma, iteration, damping, and generator matrix G) most easily affect the embedding efficiency of the algorithm. Furthermore, the method proposed by Richardson was used to design a new low-density generator matrix [2] (LDGM). Overall, simulations were performed to suboptimal parametric values, and possible combinations were simulated using LDGM with various embedding rates. The goal was to identify the optimal parametric values under various experimental data. In addition, regarding the BiP algorithm, a damping method that involves using arithmetic averages was proposed to reduce the computation complexity than that of the original damping procedure.
Книги з теми "Density embedding"
Guhr, Thomas. Replica approach in random matrix theory. Edited by Gernot Akemann, Jinho Baik, and Philippe Di Francesco. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198744191.013.8.
Повний текст джерелаЧастини книг з теми "Density embedding"
Wouters, Sebastian, Carlos A. Jiménez-Hoyos, and Garnet K.L. Chan. "Five Years of Density Matrix Embedding Theory." In Fragmentation, 227–43. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119129271.ch8.
Повний текст джерелаYu, Kuang, Caroline M. Krauter, Johannes M. Dieterich, and Emily A. Carter. "Density and Potential Functional Embedding: Theory and Practice." In Fragmentation, 81–117. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119129271.ch2.
Повний текст джерелаBarbaglia, Luca, Sergio Consoli, and Sebastiano Manzan. "Exploring the Predictive Power of News and Neural Machine Learning Models for Economic Forecasting." In Mining Data for Financial Applications, 135–49. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66981-2_11.
Повний текст джерелаWesolowski, Tomasz A. "Chapter 8. Hohenberg–Kohn Theorems as a basis for Multi-scale Simulations: Frozen-density Embedding Theory." In Theoretical and Computational Chemistry Series, 227–53. Cambridge: Royal Society of Chemistry, 2021. http://dx.doi.org/10.1039/9781839164668-00227.
Повний текст джерелаDas, Sourav, and Solomon Tesfamariam. "Reliability Based Design Optimization of Damped-Outrigger Timber Structure Using Stochastic Spectral Embedding Based Probability Density Evolution Method." In Lecture Notes in Civil Engineering, 273–84. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-21187-4_22.
Повний текст джерелаFradelos, Georgios, Jesse J. Lutz, Tomasz A. Wesołowski, Piotr Piecuch, and Marta Włoch. "Shifts in Excitation Energies Induced by Hydrogen Bonding: A Comparison of the Embedding and Supermolecular Time-Dependent Density Functional Theory Calculations with the Equation-of-Motion Coupled-Cluster Results." In Advances in the Theory of Quantum Systems in Chemistry and Physics, 219–48. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-2076-3_13.
Повний текст джерелаThebaud, Thomas, Gaël Le Lan, and Anthony Larcher. "Unsupervised Labelling of Stolen Handwritten Digit Embeddings with Density Matching." In Lecture Notes in Computer Science, 545–63. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61638-0_30.
Повний текст джерелаLee, Junghyuk, and Jong-Seok Lee. "TREND: Truncated Generalized Normal Density Estimation of Inception Embeddings for GAN Evaluation." In Lecture Notes in Computer Science, 87–103. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20050-2_6.
Повний текст джерелаNeugebauer, Johannes. "Orbital-Free Embedding Calculations of Electronic Spectra." In Recent Progress in Orbital-free Density Functional Theory, 323–54. WORLD SCIENTIFIC, 2013. http://dx.doi.org/10.1142/9789814436731_0011.
Повний текст джерелаGritsenko, O. V. "On the Principal Difference Between the Exact and Approximate Frozen-Density Embedding Theory." In Recent Progress in Orbital-free Density Functional Theory, 355–65. WORLD SCIENTIFIC, 2013. http://dx.doi.org/10.1142/9789814436731_0012.
Повний текст джерелаТези доповідей конференцій з теми "Density embedding"
Zhou, Chunting, Xuezhe Ma, Di Wang, and Graham Neubig. "Density Matching for Bilingual Word Embedding." In Proceedings of the 2019 Conference of the North. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/n19-1161.
Повний текст джерелаGuo, Xueping, Xia Zhang, Jing Zhou, Liqiang Cao, and Lixi Wan. "Thermal management and characterization of the active component embedding into organic substrate." In High Density Packaging (ICEPT-HDP). IEEE, 2011. http://dx.doi.org/10.1109/icept.2011.6067033.
Повний текст джерелаGuo, Senhui, Jing Xu, Dapeng Chen, Chao Zhang, Xiaogang Wang, and Rui Zhao. "Density-Aware Feature Embedding for Face Clustering." In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2020. http://dx.doi.org/10.1109/cvpr42600.2020.00673.
Повний текст джерелаSawlani, Saurabh, Lingxiao Zhao, and Leman Akoglu. "Fast Attributed Graph Embedding via Density of States." In 2021 IEEE International Conference on Data Mining (ICDM). IEEE, 2021. http://dx.doi.org/10.1109/icdm51629.2021.00067.
Повний текст джерелаSriperumbudur, Bharath K. "Mixture density estimation via Hilbert space embedding of measures." In 2011 IEEE International Symposium on Information Theory - ISIT. IEEE, 2011. http://dx.doi.org/10.1109/isit.2011.6033685.
Повний текст джерелаXu, Pinghua, Yibing Zhan, Liu Liu, Baosheng Yu, Bo Du, Jia Wu, and Wenbin Hu. "Dual-branch Density Ratio Estimation for Signed Network Embedding." In WWW '22: The ACM Web Conference 2022. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3485447.3512171.
Повний текст джерелаXu, Pinghua, Yibing Zhan, Liu Liu, Baosheng Yu, Bo Du, Jia Wu, and Wenbin Hu. "Dual-branch Density Ratio Estimation for Signed Network Embedding." In WWW '22: The ACM Web Conference 2022. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3485447.3512171.
Повний текст джерелаBustos-Brinez, Oscar, Joseph Gallego, and Fabio Gonzalez. "Anomaly Detection through Density Matrices and Kernel Density Estimation (AD-DMKDE)." In LatinX in AI at Neural Information Processing Systems Conference 2022. Journal of LatinX in AI Research, 2022. http://dx.doi.org/10.52591/lxai2022112810.
Повний текст джерелаWang, Baoyan, Jian Zhang, Fanggui Ding, and Yuexian Zou. "Multi-document news summarization via paragraph embedding and density peak clustering." In 2017 International Conference on Asian Language Processing (IALP). IEEE, 2017. http://dx.doi.org/10.1109/ialp.2017.8300593.
Повний текст джерелаZhou, Yang, Amnay Amimeur, Chao Jiang, Dejing Dou, Ruoming Jin, and Pengwei Wang. "Density-aware Local Siamese Autoencoder Network Embedding with Autoencoder Graph Clustering." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8621992.
Повний текст джерелаЗвіти організацій з теми "Density embedding"
Chen, Jiankun, Yingming Gu, Lihong Yin, Minyi He, Na Liu, Yue Lu, Changcai Xie, Jiqiang Li, and Yu Chen. Network meta-analysis of curative efficacy of different acupuncture methods on obesity combined with insulin resistance. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, August 2022. http://dx.doi.org/10.37766/inplasy2022.8.0075.
Повний текст джерела