Non-negative tensor factorization workflow for time series biomedical data [PDF]
STAR Protocols, 2023 Summary: Non-negative tensor factorization (NTF) enables the extraction of a small number of latent components from high-dimensional biomedical data. However, NTF requires many steps, which is a hurdle to implementation.
Koki Tsuyuzaki +4 more
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Detecting the community structure and activity patterns of temporal networks: a non-negative tensor factorization approach. [PDF]
PLoS ONE, 2014 The increasing availability of temporal network data is calling for more research on extracting and characterizing mesoscopic structures in temporal networks and on relating such structure to specific functions or properties of the system. An outstanding
Laetitia Gauvin +2 more
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Model Selection for Non-Negative Tensor Factorization with Minimum Description Length [PDF]
Entropy, 2019 Non-negative tensor factorization (NTF) is a widely used multi-way analysis approach that factorizes a high-order non-negative data tensor into several non-negative factor matrices.
Yunhui Fu +2 more
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Non-Negative Tensor Factorization Applied to Music Genre Classification [PDF]
IEEE Transactions on Audio, Speech, and Language Processing, 2010 Music genre classification techniques are typically applied to the data matrix whose columns are the feature vectors extracted from music recordings.
Benetos, E., Kotropoulos, C.
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Detecting time-evolving phenotypic components of adverse reactions against BNT162b2 SARS-CoV-2 vaccine via non-negative tensor factorization [PDF]
iScience, 2022 Summary: Symptoms of adverse reactions to vaccines evolve over time, but traditional studies have focused only on the frequency and intensity of symptoms.
Kei Ikeda +16 more
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Navigating the Functional Landscape of Transcription Factors via Non-Negative Tensor Factorization Analysis of MEDLINE Abstracts [PDF]
Frontiers in Bioengineering and Biotechnology, 2017 In this study, we developed and evaluated a novel text-mining approach, using non-negative tensor factorization (NTF), to simultaneously extract and functionally annotate transcriptional modules consisting of sets of genes, transcription factors (TFs ...
Sujoy Roy +9 more
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Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data [PDF]
, 2015 We present a Bayesian non-negative tensor factorization model for count-valued tensor data, and develop scalable inference algorithms (both batch and online) for dealing with massive tensors.
DB Dunson +6 more
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Approximate L0 constrained Non-negative Matrix and Tensor Factorization [PDF]
2008 IEEE International Symposium on Circuits and Systems (ISCAS), 2008 Non-negative matrix factorization (NMF), i.e. V = WH where both V, W and H are non-negative has become a widely used blind source separation technique due to its part based representation. The NMF decomposition is not in general unique and a part based representation not guaranteed.
Hansen, Lars Kai +2 more
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Biomechanical Modeling, Muscle Synergy-Based Rehabilitation Assessment, and Real-Time Fatigue Monitoring for Piano-Integrated Upper Limb Therapy [PDF]
BiomimeticsPiano-based occupational therapy has emerged as an engaging and effective rehabilitation strategy for improving upper limb motor functions. However, a lack of comprehensive biomechanical modeling, objective rehabilitation assessment, and real-time ...
Xin Zhao +6 more
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Spatial Low-Rank Tensor Factorization and Unmixing of Hyperspectral Images
Computers, 2021 This work presents a method for hyperspectral image unmixing based on non-negative tensor factorization. While traditional approaches may process spectral information without regard for spatial structures in the dataset, tensor factorization preserves ...
William Navas-Auger, Vidya Manian
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