| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Dong Ouyang, Yong Liang, Jinfeng Wang, Le Li, Ning Ai, Junning Feng, Shanghui Lu, Shuilin Liao, Xiaoying Liu, Shengli Xi. HGCLAMIR: Hypergraph contrastive learning with attention mechanism and integrated multi-view representation for predicting miRNA-disease associations. PLoS computational biology. vol 20. issue 4. 2024-04-23. PMID:38652712. |
finally, the integrated representation information was fed into a neural network-based matrix completion method to perform mirna-disease association prediction. |
2024-04-23 |
2024-04-26 |
human |
| G Madureira, B Mion, B Van Winters, F Peñagaricano, J Li, E S Ribeir. Endometrial responsiveness to interferon-tau and its association with subsequent reproductive performance in dairy heifers. Journal of dairy science. 2024-04-20. PMID:38642656. |
analysis of endometrial transcriptome between hf and sf heifers revealed important differences in the expression of proteins associated with cell signaling, metabolism, attachment, and migration, with a large representation of genes encoding extracellular matrix proteins. |
2024-04-20 |
2024-04-23 |
cattle |
| Louis N Irwi. Behavioral indicators of heterogeneous subjective experience in animals across the phylogenetic spectrum: Implications for comparative animal phenomenology. Heliyon. vol 10. issue 7. 2024-04-16. PMID:38623251. |
diagrams of the matrix constructed from the three qualitative modes and three quantitative attributes for each mode provide a metaphorical representation of the unique experiential profile of each species. |
2024-04-16 |
2024-04-18 |
Not clear |
| Hui Liu, Feng Wang, Jian Yu, Yong Pan, Chaoju Gong, Liang Zhang, Lin Zhan. DBDNMF: A Dual Branch Deep Neural Matrix Factorization method for drug response prediction. PLoS computational biology. vol 20. issue 4. 2024-04-04. PMID:38574114. |
dbdnmf learns the latent representation of drugs and cell lines through flexible inputs and reconstructs the partially observed matrix through a series of hidden neural network layers. |
2024-04-04 |
2024-04-07 |
Not clear |
| Thorsten Hempel, Ahmed A Abdelrahman, Ayoub Al-Hamad. Towards Robust and Unconstrained Full Range of Rotation Head Pose Estimation. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. vol PP. 2024-03-22. PMID:38512742. |
we address the issue of ambiguous rotation labels by introducing the rotation matrix formalism for our ground truth data and propose a continuous 6d rotation matrix representation for efficient and robust direct regression. |
2024-03-22 |
2024-03-24 |
Not clear |
| Fatemeh Rafiei, Hojjat Zeraati, Karim Abbasi, Parvin Razzaghi, Jahan B Ghasemi, Mahboubeh Parsaeian, Ali Masoudi-Neja. CFSSynergy: Combining Feature-Based and Similarity-Based Methods for Drug Synergy Prediction. Journal of chemical information and modeling. 2024-03-22. PMID:38514966. |
then, the new cell line representation is computed by multiplying the protein-protein similarity matrix and the initial cell line representation. |
2024-03-22 |
2024-03-24 |
Not clear |
| Rui Wang, Xiao-Jun Wu, Ziheng Chen, Cong Hu, Josef Kittle. SPD Manifold Deep Metric Learning for Image Set Classification. IEEE transactions on neural networks and learning systems. vol PP. 2024-03-13. PMID:38470600. |
specifically, smdml first selects a prevailing spd manifold neural network (spdnet) as the backbone (encoder) to derive an spd matrix nonlinear representation. |
2024-03-13 |
2024-03-15 |
Not clear |
| Robin Ristl, Heiko Götte, Armin Schüler, Martin Posch, Franz Köni. Simultaneous inference procedures for the comparison of multiple characteristics of two survival functions. Statistical methods in medical research. 2024-03-11. PMID:38465602. |
by using the counting process representation of the mentioned parameters, we show that their estimates are asymptotically multivariate normal and we provide an estimate for their covariance matrix. |
2024-03-11 |
2024-03-14 |
Not clear |
| Fuli Wang, Karelia Pena-Pena, Wei Qian, Gonzalo R Arc. T-HyperGNNs: Hypergraph Neural Networks via Tensor Representations. IEEE transactions on neural networks and learning systems. vol PP. 2024-03-08. PMID:38451750. |
in this article, we depart from hypergraph matrix representations and present a new tensor-hypergnn (t-hypergnn) framework with cross-node interactions (cnis). |
2024-03-08 |
2024-03-10 |
Not clear |
| Jiayang Jiang, Ming Zhang, Aosheng Gu, R J Dwayne Miller, Zheng L. Quantum tomography of molecules using ultrafast electron diffraction. The Journal of chemical physics. vol 160. issue 10. 2024-03-08. PMID:38456529. |
from the simulated time-resolved diffraction data, we retrieve the evolving density matrix in a crude diabatic representation basis and reveal the symmetry of the excited pyrrole wavepacket. |
2024-03-08 |
2024-03-10 |
Not clear |
| Jinrong Cui, Zhipeng He, Qiong Huang, Yulu Fu, Yuting Li, Jie We. Structure-aware contrastive hashing for unsupervised cross-modal retrieval. Neural networks : the official journal of the International Neural Network Society. vol 174. 2024-03-06. PMID:38447425. |
specifically, we concurrently employ both high-dimensional representations and discriminative representations learned by the network to construct a more informative semantic correlative matrix across modalities. |
2024-03-06 |
2024-03-09 |
Not clear |
| Xin Cao, Jia Li, Panpan Zhao, Jiachen Li, Xueying Qi. Corr-Track: Category-Level 6D Pose Tracking with Soft-Correspondence Matrix Estimation. IEEE transactions on visualization and computer graphics. vol PP. 2024-03-05. PMID:38437129. |
we first introduce a soft correspondence matrix for pose tracking tasks and establish effective constraints through direct spatial point-to-point correspondence representations in the sparse point cloud correspondence matrix. |
2024-03-05 |
2024-03-07 |
Not clear |
| Abdullah A Asiri, Ahmad Shaf, Tariq Ali, Muhammad Ahmad Pasha, Aiza Khan, Muhammad Irfan, Saeed Alqahtani, Ahmad Alghamdi, Ali H Alghamdi, Abdullah Fahad A Alshamrani, Magbool Alelyani, Sultan Alamr. Advancing brain tumor detection: harnessing the Swin Transformer's power for accurate classification and performance analysis. PeerJ. Computer science. vol 10. 2024-03-04. PMID:38435590. |
utilizing 21 matrices for performance evaluation across all four classes, these matrices provide a detailed insight into the model's behavior throughout the learning process, furthermore showcasing a graphical representation of confusion matrix, training and validation loss and accuracy. |
2024-03-04 |
2024-03-06 |
Not clear |
| Petra Csizmadia, Boglárka Nagy, Lili Kővári, Zsófia Anna Gaá. Exploring the role of working memory gate opening process in creativity: An ERP study using the reference-back paradigm. Biological psychology. 2024-02-28. PMID:38417665. |
our results suggest that groups with different levels of convergent thinking (based on matrix reasoning) and those with lower dt (based on creativity index) tend to select and activate the prefrontal cortex representation containing the required task information at an earlier stage, compared to those with better dt. |
2024-02-28 |
2024-03-02 |
Not clear |
| Junhua Zeng, Yuning Qiu, Yumeng Ma, Andong Wang, Qibin Zha. A Novel Tensor Ring Sparsity Measurement for Image Completion. Entropy (Basel, Switzerland). vol 26. issue 2. 2024-02-23. PMID:38392360. |
the matrix rank, served as a measure of data sparsity, quantifies the sparsity within the kronecker basis representation of a given piece of data in the matrix format. |
2024-02-23 |
2024-02-25 |
Not clear |
| Junhua Zeng, Yuning Qiu, Yumeng Ma, Andong Wang, Qibin Zha. A Novel Tensor Ring Sparsity Measurement for Image Completion. Entropy (Basel, Switzerland). vol 26. issue 2. 2024-02-23. PMID:38392360. |
nevertheless, in practical scenarios, much of the data are intrinsically multi-dimensional, and thus, using a matrix format for data representation will inevitably yield sub-optimal outcomes. |
2024-02-23 |
2024-02-25 |
Not clear |
| Junhua Zeng, Yuning Qiu, Yumeng Ma, Andong Wang, Qibin Zha. A Novel Tensor Ring Sparsity Measurement for Image Completion. Entropy (Basel, Switzerland). vol 26. issue 2. 2024-02-23. PMID:38392360. |
this metric relies on the tensor ring (tr) kronecker basis representation of the tensor, providing a unified interpretation akin to matrix sparsity measurements, wherein the kronecker basis serves as the foundational representation component. |
2024-02-23 |
2024-02-25 |
Not clear |
| G Dheepak, Anita Christaline J, D Vaishal. Brain tumor classification: a novel approach integrating GLCM, LBP and composite features. Frontiers in oncology. vol 13. 2024-02-14. PMID:38352298. |
integrating glcm (gray-level co-occurrence matrix) and lbp (local binary patterns) features offers a comprehensive representation of texture characteristics, enhancing tumor detection and classification precision. |
2024-02-14 |
2024-02-16 |
Not clear |
| Haipeng Zhao, Baozhong Zhu, Tengsheng Jiang, Zhiming Cui, Hongjie W. Identification of DNA-protein binding residues through integration of Transformer encoder and Bi-directional Long Short-Term Memory. Mathematical biosciences and engineering : MBE. vol 21. issue 1. 2024-02-02. PMID:38303418. |
in the context of protein representation, we combine the evolutionary information of the protein, represented by its position-specific scoring matrix, with the spatial information of the protein's secondary structure, enriching the overall informational content. |
2024-02-02 |
2024-02-04 |
Not clear |
| Wenming Wu, Xiaoke Ma, Quan Wang, Maoguo Gong, Quanxue Ga. Learning deep representation and discriminative features for clustering of multi-layer networks. Neural networks : the official journal of the International Neural Network Society. vol 170. 2024-01-19. PMID:38029721. |
specifically, drdf learns the deep representation with deep nonnegative matrix factorization, where the high-order topology of the multi-layer network is gradually and precisely characterized. |
2024-01-19 |
2024-01-22 |
Not clear |