| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Deqing Wang, Baoyu Jing, Chenwei Lu, Junjie Wu, Guannan Liu, Chenguang Du, Fuzhen Zhuan. Coarse Alignment of Topic and Sentiment: A Unified Model for Cross-Lingual Sentiment Classification. IEEE transactions on neural networks and learning systems. vol 32. issue 2. 2021-09-23. PMID:32287008. |
existing feature representation learning-based approaches try to minimize the difference of latent features between different domains by exact alignment, which is achieved by either one-to-one topic alignment or matrix projection. |
2021-09-23 |
2023-08-13 |
Not clear |
| Hongfei Li, Chuandong Li, Deqiang Ouyang, Sing Kiong Nguan. Impulsive Synchronization of Unbounded Delayed Inertial Neural Networks With Actuator Saturation and Sampled-Data Control and its Application to Image Encryption. IEEE transactions on neural networks and learning systems. vol 32. issue 4. 2021-09-23. PMID:32310799. |
by applying polytopic representation technique, the actuator saturation term is first considered into the design of impulsive controller, and less conservative linear matrix inequality (lmi) criteria that guarantee asymptotical synchronization for the considered model via hybrid control are given. |
2021-09-23 |
2023-08-13 |
Not clear |
| Cheng Yao, Dewen Cheng, Yongtian Wan. Matrix optics representation and imaging analysis of a light-field near-eye display. Optics express. vol 28. issue 26. 2021-09-17. PMID:33379535. |
matrix optics representation and imaging analysis of a light-field near-eye display. |
2021-09-17 |
2023-08-13 |
Not clear |
| Bagayalakshmi Karuna Nidhi Muthugobal, Ganapathy Ramesh, Subbiah Parthasarathy, Suvaiyarasan Suvaithenamudhan, Karuppasamy Muthuvel Prasat. Gray code representation of the universal genetic code: Generation of never born protein sequences using Toeplitz matrix approach. Bio Systems. vol 198. 2021-09-09. PMID:33161051. |
gray code representation of the universal genetic code: generation of never born protein sequences using toeplitz matrix approach. |
2021-09-09 |
2023-08-13 |
Not clear |
| Bagayalakshmi Karuna Nidhi Muthugobal, Ganapathy Ramesh, Subbiah Parthasarathy, Suvaiyarasan Suvaithenamudhan, Karuppasamy Muthuvel Prasat. Gray code representation of the universal genetic code: Generation of never born protein sequences using Toeplitz matrix approach. Bio Systems. vol 198. 2021-09-09. PMID:33161051. |
we use this gray code and partitioned gray code representations of the universal genetic code combined with the novel toeplitz matrix approach to generate many never born protein (nbp) sequences, which exhibit intrinsic structural stability. |
2021-09-09 |
2023-08-13 |
Not clear |
| Zhiqiang Tao, Jun Li, Huazhu Fu, Yu Kong, Yun F. From Ensemble Clustering to Subspace Clustering: Cluster Structure Encoding. IEEE transactions on neural networks and learning systems. vol PP. 2021-09-08. PMID:34495848. |
first, the low-rank representation (lrr) is learned from a higher order data relationship induced by ensemble k-means coding, which exploits the cluster structure in a co-association matrix of basic partitions (i.e., clustering results). |
2021-09-08 |
2023-08-13 |
Not clear |
| Akshatha Prasanna, Vidya Niranja. MutVis: Automated framework for analysis and visualization of mutational signatures in pathogenic bacterial strains. Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases. vol 91. 2021-09-06. PMID:33689914. |
mutvis supports variant calling, transition (ti) and transversion (tv) graphical representation, generation of mutational count matrix, graphical visualization of base-pair substitution spectrum (bpss) and mutation signatures extraction. |
2021-09-06 |
2023-08-13 |
Not clear |
| Sehwan Moon, Hyunju Le. JDSNMF: Joint Deep Semi-Non-Negative Matrix Factorization for Learning Integrative Representation of Molecular Signals in Alzheimer's Disease. Journal of personalized medicine. vol 11. issue 8. 2021-08-31. PMID:34442330. |
jdsnmf: joint deep semi-non-negative matrix factorization for learning integrative representation of molecular signals in alzheimer's disease. |
2021-08-31 |
2023-08-13 |
human |
| Bao-Yu Liu, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Philip S Y. Multiview Clustering via Proximity Learning in Latent Representation Space. IEEE transactions on neural networks and learning systems. vol PP. 2021-08-27. PMID:34432638. |
for another, through conducting the latent representation learning and consensus proximity learning simultaneously, mlpl learns a consensus proximity matrix with k connected components to output the clustering result directly. |
2021-08-27 |
2023-08-13 |
Not clear |
| Mulin Chen, Maoguo Gong, Xuelong L. Feature Weighted Non-Negative Matrix Factorization. IEEE transactions on cybernetics. vol PP. 2021-08-26. PMID:34437084. |
non-negative matrix factorization (nmf) is one of the most popular techniques for data representation and clustering and has been widely used in machine learning and data analysis. |
2021-08-26 |
2023-08-13 |
Not clear |
| Adam Winchell, Andrew Lan, Michael Moze. Highlights as an Early Predictor of Student Comprehension and Interests. Cognitive science. vol 44. issue 11. 2021-08-23. PMID:33191526. |
using multiple representations of the highlighting patterns, we built probabilistic models to predict quiz performance and matrix factorization models to predict what content would be highlighted in one passage from highlights in other passages. |
2021-08-23 |
2023-08-13 |
human |
| Onur Çaylak, Björn Baumeie. Machine Learning of Quasiparticle Energies in Molecules and Clusters. Journal of chemical theory and computation. vol 17. issue 8. 2021-08-14. PMID:34314186. |
coulomb matrix, bag-of-bond, and bond-angle-torsion representations are made orbital-sensitive by augmenting them with atom-centered orbital charges and kohn-sham orbital energies, both of which are readily available from baseline calculations at the level of density functional theory (dft). |
2021-08-14 |
2023-08-13 |
Not clear |
| Miguel Angel Funes-Lora, Brian J Thelen, Albert J Shih, James Hamilton, Nirmala Rajaram, Jingxuan Lyu, Yihao Zheng, Timothy Morgan, William F Weitze. Ultrasound Measurement of Vascular Distensibility Based on Edge Detection and Speckle Tracking Using Ultrasound DICOM Data. ASAIO journal (American Society for Artificial Internal Organs : 1992). 2021-08-12. PMID:34380948. |
canny edge detector, vandermonde matrix representation, kanade lucas tomasi algorithm with pyramidal segmentation, and penalized least squares technique identifies the vessel lumen edge, track the vessel diameter, detrend the signal and find peaks and valleys when the vessel is fully distended or contracted. |
2021-08-12 |
2023-08-13 |
Not clear |
| Aymeric Le Gratiet, Luca Lanzano, Artemi Bendandi, Riccardo Marongiu, Paolo Bianchini, Colin Sheppard, Alberto Diaspr. Phasor approach of Mueller matrix optical scanning microscopy for biological tissue imaging. Biophysical journal. vol 120. issue 15. 2021-08-11. PMID:34224693. |
in this work, we propose a new, to our knowledge, representation dedicated to the study of biological tissues that combines mueller matrix microscopy with a phasor approach. |
2021-08-11 |
2023-08-13 |
Not clear |
| Anthony Steed, Eyal Ofek, Mike Sinclair, Mar Gonzalez-Franc. A mechatronic shape display based on auxetic materials. Nature communications. vol 12. issue 1. 2021-08-10. PMID:34362893. |
besides their complexity and high cost, these matrix displays suffer from sharp edges due to the discreet representation which reduces their ability to render a large continuous surface when sliding the hand. |
2021-08-10 |
2023-08-13 |
Not clear |
| Meenu Gupta, Hao Wu, Simrann Arora, Akash Gupta, Gopal Chaudhary, Qiaozhi Hu. Gene Mutation Classification through Text Evidence Facilitating Cancer Tumour Detection. Journal of healthcare engineering. vol 2021. 2021-08-10. PMID:34367540. |
three machine learning classification models, namely, logistic regression (lr), random forest (rf), and xgboost (xgb), along with the recurrent neural network (rnn) model of deep learning, are applied to the sparse matrix (keywords count representation) of text descriptions. |
2021-08-10 |
2023-08-13 |
Not clear |
| Zhikui Chen, Shan Jin, Runze Liu, Jianing Zhan. A Deep Non-negative Matrix Factorization Model for Big Data Representation Learning. Frontiers in neurorobotics. vol 15. 2021-08-07. PMID:34354579. |
a deep non-negative matrix factorization model for big data representation learning. |
2021-08-07 |
2023-08-13 |
Not clear |
| Zhikui Chen, Shan Jin, Runze Liu, Jianing Zhan. A Deep Non-negative Matrix Factorization Model for Big Data Representation Learning. Frontiers in neurorobotics. vol 15. 2021-08-07. PMID:34354579. |
to alleviate the challenge, a deep matrix factorization method with non-negative constraints is proposed to learn deep part-based representations of interpretability for big data in this paper. |
2021-08-07 |
2023-08-13 |
Not clear |
| Zhikui Chen, Shan Jin, Runze Liu, Jianing Zhan. A Deep Non-negative Matrix Factorization Model for Big Data Representation Learning. Frontiers in neurorobotics. vol 15. 2021-08-07. PMID:34354579. |
furthermore, to train the deep matrix factorization architecture, an interpretability loss is defined, including a symmetric loss, an apposition loss, and a non-negative constraint loss, which can ensure the knowledge transfer from the supervisor network to the student network, enhancing the robustness of deep representations. |
2021-08-07 |
2023-08-13 |
Not clear |
| Ying Guo, Yan-Fang Wang, Sheng-Li Zhan. A novel way to numerically characterize DNA sequences and its application. International journal of quantum chemistry. vol 111. issue 14. 2021-08-04. PMID:32327765. |
instead of calculating the leading eigenvalues of the matrix for graphical representation, we computed curvature and torsion of curves as the descriptor to numerically characterize dna sequences. |
2021-08-04 |
2023-08-13 |
Not clear |