This report focuses on so-called weighted variants of nonnnegative matrix factorization (NMF) and more generally nonnnegative tensor factorization (NTF) approximations. First, we consider multiplicative update (MU) rules to optimize these approximations,
Chevallier, Louis +2 more
core
Limestone: high-throughput candidate phenotype generation via tensor factorization. [PDF]
Ho JC +6 more
europepmc +1 more source
Peak picking NMR spectral data using non-negative matrix factorization. [PDF]
Tikole S +4 more
europepmc +1 more source
Munc13-1 couples DAG and Ca<sup>2+</sup> signaling to dynamic vesicle priming, synaptic short-term plasticity, and posttetanic potentiation. [PDF]
Ranjan M +10 more
europepmc +1 more source
Advances in nonnegative matrix and tensor factorization. [PDF]
Cichocki A +4 more
europepmc +1 more source
This work proposes a solution to the problem of under-determined audio source separation using pre-trained redundant source-based prior information.
Svaizer, Piergiorgio +2 more
core
The AMEE-PPI Method to Extract Typical Outcrop Endmembers from GF-5 Hyperspectral Images. [PDF]
Hu L +6 more
europepmc +1 more source
HYPERSPECTRAL AUTOFLUORESCENCE IMAGING OF DRUSEN AND RETINAL PIGMENT EPITHELIUM IN DONOR EYES WITH AGE-RELATED MACULAR DEGENERATION. [PDF]
Tong Y +8 more
europepmc +1 more source
Interpretable and Federated Tensor Factorization for Computational Phenotyping
DoctorPhenotyping based on machine learning has been proposed to facilitate extraction of meaningful phenotypes automatically from electronic health records (EHRs) without human supervision through a process called computational phenotyping.
김예진
core
Probabilistic latent variable models as nonnegative factorizations. [PDF]
Shashanka M, Raj B, Smaragdis P.
europepmc +1 more source

