Suchergebnisse - "convex non-negative matrix factorization"

On the Relation Between Linear Autoencoders and Non-Negative Matrix Factorization for Mutational Signature Extraction

Autoren: Ida Egendal Rasmus Froberg Brøndum Marta Pelizzola et al.

Quelle: Egendal, I, Brøndum, R F, Pelizzola, M, Hobolth, A & Bøgsted, M 2025, 'On the Relation Between Linear Autoencoders and Non-Negative Matrix Factorization for Mutational Signature Extraction', Journal of Computational Biology, vol. 32, no. 5, pp. 461-472. https://doi.org/10.1089/cmb.2024.0784
Egendal, I, Brøndum, R F, Pelizzola, M, Hobolth, A & Bøgsted, M 2025, 'On the Relation Between Linear Autoencoders and Non-Negative Matrix Factorization for Mutational Signature Extraction', Journal of computational biology : a journal of computational molecular cell biology, vol. 32, no. 5, pp. 461-472. https://doi.org/10.1089/cmb.2024.0784

Schlagwörter: non-negative matrix factorization, convex non-negative matrix factorization, mutational signatures, non-negative autoencoders

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/40113251

Temporal Community Detection and Analysis with Network Embeddings

Autoren: Limengzi Yuan Xuanming Zhang Yuxian Ke et al.

Quelle: Mathematics ; Volume 13 ; Issue 5 ; Pages: 698

Schlagwörter: temporal community detection, social networks, network embedding, evolutionary clustering, convex non-negative matrix factorization

Dateibeschreibung: application/pdf

Relation: E1: Mathematics and Computer Science; https://dx.doi.org/10.3390/math13050698

Verfügbarkeit: https://doi.org/10.3390/math13050698

Early pseudoprogression and progression lesions in glioblastoma patients are both metabolically heterogeneous

Autoren: Gülnur Ungan Albert Pons‐Escoda Daniel Ulinic et al.

Weitere Verfasser: Gülnur Ungan Albert Pons‐Escoda Daniel Ulinic et al.

Quelle: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Dipòsit Digital de Documents de la UAB
Universitat Autònoma de Barcelona

Schlagwörter: MRS, Brain Neoplasms, Àrees temàtiques de la UPC::Ciències de la salut, Convex non-negative matrix factorization, Mètodes analítics matricials, Chemoradiotherapy, MR, Glioblastoma multiforme, Magnetic Resonance Imaging, 3. Good health, Dacarbazine, 03 medical and health sciences, 0302 clinical medicine, Matrix analytic methods, Pseudoprogression, Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi matemàtica, Disease Progression, Humans, Glioblastoma, Follow-Up Studies, Retrospective Studies

Dateibeschreibung: application/pdf

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/38213096
https://ddd.uab.cat/record/287426
https://hdl.handle.net/2117/401582
https://doi.org/10.1002/nbm.5095

Clustering of cell populations in flow cytometry data using a combination of Gaussian mixtures

Autoren: Michael Reiter Paolo Rota Florian Kleber et al.

Quelle: Pattern Recognition. 60:1029-1040

Schlagwörter: 0301 basic medicine, 0303 health sciences, 03 medical and health sciences, Acute lymphblastic leukemia, Clustering, Convex non-negative matrix factorization, Flow cytometry, Gaussian mixture model, L2 distance

Zugangs-URL: https://dl.acm.org/doi/10.1016/j.patcog.2016.04.004
https://doi.org/10.1016/j.patcog.2016.04.004
https://dblp.uni-trier.de/db/journals/pr/pr60.html#ReiterRKDGD16
https://www.sciencedirect.com/science/article/pii/S0031320316300371
https://ui.adsabs.harvard.edu/abs/2016PatRe..60.1029R/abstract
https://hdl.handle.net/11572/251848
https://doi.org/10.1016/j.patcog.2016.04.004

Automated quality control for proton magnetic resonance spectroscopy data using convex non-negative matrix factorization

Autoren: Mocioiu, Victor Kyathanahally, Sreenath P. Arús, Carles et al.

Weitere Verfasser: Mocioiu, Victor Kyathanahally, Sreenath P. Arús, Carles et al.

Schlagwörter: Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic, Decision support systems, Brain -- Tumors -- Diagnosis, Brain tumors, Magnetic resonance spectroscopy, Convex non-negative matrix factorization, Pattern recognition, Quality control, Machine learning, Sistemes d'ajuda a la decisió, Cervell -- Tumors -- Diagnòstic

Dateibeschreibung: 9 p.; application/pdf

Relation: http://link.springer.com/chapter/10.1007%2F978-3-319-31744-1_62; http://hdl.handle.net/2117/99395

Verfügbarkeit: http://hdl.handle.net/2117/99395
https://doi.org/10.1007/978-3-319-31744-1_62

Discriminant Convex Non-negative Matrix Factorization for the classification of human brain tumours

Autoren: Vilamala Muñoz, Albert Lisboa, Paulo J G Ortega Martorell, Sandra et al.

Weitere Verfasser: Vilamala Muñoz, Albert Lisboa, Paulo J G Ortega Martorell, Sandra et al.

Quelle: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Recercat. Dipósit de la Recerca de Catalunya
instname

Schlagwörter: Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC], Tumors -- Diagnosis, Discriminant Convex Non-negative Matrix Factorization, 03 medical and health sciences, 0302 clinical medicine, Brain tumours, Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica, Magnetic resonance spectroscopy, 0202 electrical engineering, electronic engineering, information engineering, Source separation, 02 engineering and technology, Tumors -- Models matemàtics

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/2117/20446
https://dblp.uni-trier.de/db/journals/prl/prl34.html#VilamalaLOV13
https://www.sciencedirect.com/science/article/pii/S0167865513002213
http://ui.adsabs.harvard.edu/abs/2013PaReL..34.1734V/abstract
https://upcommons.upc.edu/handle/2117/20446
https://core.ac.uk/display/41772337
http://www.sciencedirect.com/science/article/pii/S0167865513002213

Early pseudoprogression and progression lesions in glioblastoma patients are both metabolically heterogeneous

Autoren: Universitat Politècnica de Catalunya. Departament de Ciències de la Computació Universitat Politècnica de Catalunya. IDEAI-UPC - Intelligent Data sciEnce and Artificial Intelligence Research Group Ungan, Gülnur et al.

Index Begriffe: Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi matemàtica, Àrees temàtiques de la UPC::Ciències de la salut, Matrix analytic methods, Glioblastoma multiforme, Convex non-negative matrix factorization, Glioblastoma, MR, MRS, Pseudoprogression, Mètodes analítics matricials, Article

URL: https://hdl.handle.net/2117/401582
https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/nbm.5095
https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/nbm.5095
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-104551RB-I00/ES/APRENDIZAJE AUTOMATICO PARA LA MODELIZACION DE LA DINAMICA MOLECULAR DE LAS PROTEINAS GPCR

Automated quality control for proton magnetic resonance spectroscopy data using convex non-negative matrix factorization

Autoren: Universitat Politècnica de Catalunya. Departament de Ciències de la Computació Universitat Politècnica de Catalunya. SOCO - Soft Computing Mocioiu, Victor et al.

Index Begriffe: Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic, Decision support systems, Brain -- Tumors -- Diagnosis, Brain tumors, Magnetic resonance spectroscopy, Convex non-negative matrix factorization, Pattern recognition, Quality control, Machine learning, Sistemes d'ajuda a la decisió, Cervell -- Tumors -- Diagnòstic, Conference report

URL: http://hdl.handle.net/2117/99395
http://link.springer.com/chapter/10.1007%2F978-3-319-31744-1_62
http://link.springer.com/chapter/10.1007%2F978-3-319-31744-1_62

Discriminant convex non-negative matrix factorization for the classification of human brain tumours

Autoren: Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics Universitat Politècnica de Catalunya. SOCO - Soft Computing Vilamala Muñoz, Albert et al.

Index Begriffe: Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica, Tumors -- Diagnosis, Brain tumours, Discriminant Convex Non-negative Matrix Factorization, Magnetic resonance spectroscopy, Source separation, Tumors -- Models matemàtics, Article

URL: https://hdl.handle.net/2117/20446
http://www.sciencedirect.com/science/article/pii/S0167865513002213
http://www.sciencedirect.com/science/article/pii/S0167865513002213