All Relations between representation and matrix compartment

Publication Sentence Publish Date Extraction Date Species
Francesco Di Trapani, Thomas Franosch, Michele Caragli. Active Brownian particles in a circular disk with an absorbing boundary. Physical review. E. vol 107. issue 6-1. 2023-07-19. PMID:37464643. using the passive brownian particle as basis states and dealing with the activity as a perturbation, we provide a matrix representation of the fokker-planck operator and we express the propagator in terms of the perturbed eigenvalues and eigenfunctions. 2023-07-19 2023-08-14 Not clear
Yanwu Yang, Chenfei Ye, Xutao Guo, Tao Wu, Yang Xiang, Ting M. Mapping Multi-modal Brain Connectome for Brain Disorder Diagnosis via Cross-modal Mutual Learning. IEEE transactions on medical imaging. vol PP. 2023-07-13. PMID:37440391. additionally, we investigate mutual learning in explicit and implicit ways: (1) cross-modal representations are obtained by cross-embedding explicitly based on the inter-modal correspondence matrix. 2023-07-13 2023-08-14 Not clear
Zelin Li, Wenhong Wan. Joint Learning of Correlation-Constrained Fuzzy Clustering and Discriminative Non-Negative Representation for Hyperspectral Band Selection. Sensors (Basel, Switzerland). vol 23. issue 10. 2023-07-11. PMID:37430753. in cfnr, graph regularized non-negative matrix factorization (gnmf) and constrained fuzzy c-means (fcm) are integrated into a unified model to perform clustering on the learned feature representation of bands rather than on the original high-dimensional data. 2023-07-11 2023-08-14 Not clear
Mingli Chen, Haonan Chen, Tao Han, Xiangji Ca. Disentanglement Dynamics in Nonequilibrium Environments. Entropy (Basel, Switzerland). vol 24. issue 10. 2023-07-08. PMID:37420350. the reduced density matrix of the two-qubit system can be expressed as the kraus representation in terms of the tensor products of the single qubit kraus operators. 2023-07-08 2023-08-14 Not clear
Yue Wu, Yue Zhang, Wenping Ma, Maoguo Gong, Xiaolong Fan, Mingyang Zhang, A K Qin, Qiguang Mia. RORNet: Partial-to-Partial Registration Network With Reliable Overlapping Representations. IEEE transactions on neural networks and learning systems. vol PP. 2023-06-30. PMID:37389998. different from the previous methods of direct registration after extraction of overlapping areas, rornet adds the step of extracting reliable representations before registration, where the proposed similarity matrix downsampling method is used to filter out the points with low similarity and retain reliable representations, and thus reduce the side effects of overlap estimation errors on the registration. 2023-06-30 2023-08-14 Not clear
Fei Wang, Weihao Li, Dan Wu, Lin Liu, Olga Korotkova, Yangjian Ca. Propagation of coherence-OAM matrix of an optical beam in vacuum and turbulence. Optics express. vol 31. issue 13. 2023-06-29. PMID:37381195. further, we develop a wave-optics simulation method incorporating modal representation of random beams, multi-phase screen method and the coordinate transformation to simulate propagation of the coam matrix of any partially coherent beam propagating in free space or in turbulent medium. 2023-06-29 2023-08-14 Not clear
Xin Zheng, Shenyu Dai, Shuai Zha. Partially coherent laser beam shaping in a zoom homogenizer. Optics express. vol 31. issue 11. 2023-06-29. PMID:37381555. based on the principles of pseudo-mode representation and matrix optics, a numerical model for fast simulation has been built and the parameter constraints for avoiding beamlet crosstalk have been presented. 2023-06-29 2023-08-14 Not clear
Chuan Tang, Kun Sun, Chang Tang, Xiao Zheng, Xinwang Liu, Jun-Jie Huang, Wei Zhan. Multi-view subspace clustering via adaptive graph learning and late fusion alignment. Neural networks : the official journal of the International Neural Network Society. vol 165. 2023-06-16. PMID:37327580. most of existing methods learn a sample representation coefficient matrix or an affinity graph for each single view, then the final clustering result is obtained from the spectral embedding of a consensus graph using certain traditional clustering techniques, such as k-means. 2023-06-16 2023-08-14 Not clear
Wanqi Yang, Like Xin, Lei Wang, Ming Yang, Wenzhu Yan, Yang Ga. Iterative Multiview Subspace Learning for Unpaired Multiview Clustering. IEEE transactions on neural networks and learning systems. vol PP. 2023-06-13. PMID:37310818. moreover, based on iumc, we design two effective umc methods: 1) iterative unpaired multiview clustering via covariance matrix alignment (iumc-ca) that further aligns the covariance matrix of subspace representations and then performs clustering on the subspace and 2) iterative unpaired multiview clustering via one-stage clustering assignments (iumc-cy) that performs one-stage multiview clustering (mvc) by replacing the subspace representations with clustering assignments. 2023-06-13 2023-08-14 Not clear
Xin Wang, Julian Berberich, Jian Sun, Gang Wang, Frank Allgower, Jie Che. Model-Based and Data-Driven Control of Event-and Self-Triggered Discrete-Time Linear Systems. IEEE transactions on cybernetics. vol PP. 2023-06-09. PMID:37294646. combining the model-based condition with a recent data-based system representation, a data-driven stability criterion in the form of linear matrix inequalities (lmis) is established, which also offers a way of co-designing the ets matrix and the controller. 2023-06-09 2023-08-14 Not clear
Qiang Zhang, Yaming Zheng, Qiangqiang Yuan, Meiping Song, Haoyang Yu, Yi Xia. Hyperspectral Image Denoising: From Model-Driven, Data-Driven, to Model-Data-Driven. IEEE transactions on neural networks and learning systems. vol PP. 2023-06-06. PMID:37279128. later, we comprehensively review existing hsi denoising methods, from model-driven strategy (nonlocal mean, total variation, sparse representation, low-rank matrix approximation, and low-rank tensor factorization), data-driven strategy 2-d convolutional neural network (cnn), 3-d cnn, hybrid, and unsupervised networks, to model-data-driven strategy. 2023-06-06 2023-08-14 Not clear
Stiv Llenga, Ganna Gryn'ov. Matrix of orthogonalized atomic orbital coefficients representation for radicals and ions. The Journal of chemical physics. vol 158. issue 21. 2023-06-02. PMID:37265212. matrix of orthogonalized atomic orbital coefficients representation for radicals and ions. 2023-06-02 2023-08-14 Not clear
Stiv Llenga, Ganna Gryn'ov. Matrix of orthogonalized atomic orbital coefficients representation for radicals and ions. The Journal of chemical physics. vol 158. issue 21. 2023-06-02. PMID:37265212. here, we present the matrix of orthogonalized atomic orbital coefficients (maoc) as a quantum-inspired molecular and atomic representation containing both structural (composition and geometry) and electronic (charge and spin multiplicity) information. 2023-06-02 2023-08-14 Not clear
Yunbo Tang, Dan Chen, Jia Wu, Weiping Tu, Jessica J M Monaghan, Paul Sowman, David Mcalpin. Corrigendum to "Functional Connectivity Learning via Siamese-based SPD Matrix Representation of Brain Imaging Data" [Neural Networks 163 (2023) 272-285]. Neural networks : the official journal of the International Neural Network Society. vol 164. 2023-05-25. PMID:37229929. corrigendum to "functional connectivity learning via siamese-based spd matrix representation of brain imaging data" [neural networks 163 (2023) 272-285]. 2023-05-25 2023-08-14 Not clear
Mugang Lin, Kunhui Wen, Xuanying Zhu, Huihuang Zhao, Xianfang Su. Graph Autoencoder with Preserving Node Attribute Similarity. Entropy (Basel, Switzerland). vol 25. issue 4. 2023-05-16. PMID:37190356. the cross-entropy loss of the reconstructed adjacency matrix and the mean-squared error loss of the reconstructed node attribute similarity matrix are used to update the model parameters and ensure that the node representation preserves the original structural and node attribute similarity information. 2023-05-16 2023-08-14 Not clear
Mustafa Temiz, Burcu Bakir-Gungor, Pınar Güner Şahan, Mustafa Cosku. Topological feature generation for link prediction in biological networks. PeerJ. vol 11. 2023-05-15. PMID:37187525. due to the high dimensionality of the matrix obtained after the embedding process, the data are transformed into a smaller representation by applying feature regularization techniques. 2023-05-15 2023-08-14 Not clear
Andero Uusberg, Brett Ford, Helen Uusberg, James J Gros. Reappraising reappraisal: an expanded view. Cognition & emotion. 2023-05-10. PMID:37161355. we demonstrate that the 2 × 2 × 2 matrix formed by crossing the three distinctions between reconstrual and repurposing, between object-level and meta-level representations, and between decommitment and commitment operations forms a useful map of different reappraisal tactics. 2023-05-10 2023-08-14 Not clear
Yunyun Liang, Rongguo Yang, Jing Zhang, Tiancai Zhan. Hexapartite steering based on a four-wave-mixing process with a spatially structured pump. Optics express. vol 31. issue 7. 2023-05-09. PMID:37155804. matrix representation is used to express the steerings for the first time, which is very useful to understand the monogamy relations intuitively. 2023-05-09 2023-08-14 Not clear
Cornelia L A Dewald, Alina Balandis, Lena S Becker, Jan B Hinrichs, Christian von Falck, Frank K Wacker, Hans Laser, Svetlana Gerbel, Hinrich B Winther, Johanna Apfel-Stark. Automated Classification of Free-Text Radiology Reports: Using Different Feature Extraction Methods to Identify Fractures of the Distal Fibula. RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin. 2023-05-09. PMID:37160146. this data was used to establish a machine learning pipeline, which implemented the text representation methods bag-of-words (bow), term frequency-inverse document frequency (tf-idf), principal component analysis (pca), non-negative matrix factorization (nmf), latent dirichlet allocation (lda), and document embedding (doc2vec). 2023-05-09 2023-08-14 Not clear
Jerome Riedel, Patrick Gelß, Rupert Klein, Burkhard Schmid. WaveTrain: A Python package for numerical quantum mechanics of chain-like systems based on tensor trains. The Journal of chemical physics. vol 158. issue 16. 2023-04-28. PMID:37114709. the python package is centered around tensor train (tt, or matrix product) format representations of hamiltonian operators and (stationary or time-evolving) state vectors. 2023-04-28 2023-08-14 Not clear