Výsledky vyhledávání - sparse supervised autoencoder

Detecting subtle transcriptomic perturbations induced by lncRNAs Knock-Down in single-cell CRISPRi screening using a new sparse supervised autoencoder neural network

Autoři: Marin Truchi Caroline Lacoux Cyprien Gille a další

Přispěvatelé: Marin Truchi Caroline Lacoux Cyprien Gille a další

Zdroj: Front Bioinform
Frontiers in Bioinformatics, Vol 4 (2024)

Témata: 0301 basic medicine, single-cell RNA-seq, hypoxia, Bioinformatics, Computer applications to medicine. Medical informatics, 0206 medical engineering, lncRNAs, R858-859.7, CRISPRi, 02 engineering and technology, 3. Good health, [SDV] Life Sciences [q-bio], sparse supervised autoencoder, 03 medical and health sciences, [SDV.BBM] Life Sciences [q-bio]/Biochemistry, Molecular Biology

Popis souboru: application/pdf

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38501112
https://doaj.org/article/961d2c23e9cc4a02a8c14cc9b774b873
https://amu.hal.science/hal-04883524v1
https://amu.hal.science/hal-04883524v1/document
https://doi.org/10.3389/fbinf.2024.1340339
https://hal.science/hal-04795816v1/document
https://hal.science/hal-04795816v1
https://doi.org/10.3389/fbinf.2024.1340339

Detecting subtle transcriptomic perturbations induced by lncRNAs knock-down in single-cell CRISPRi screening using a new sparse supervised autoencoder neural network

Autoři: Marin Truchi Caroline Lacoux Cyprien Gille a další

Zdroj: Frontiers in Bioinformatics, Vol 4 (2024)

Témata: single-cell RNA-seq, lncRNAs, hypoxia, CRISPRi, sparse supervised autoencoder, Computer applications to medicine. Medical informatics, R858-859.7

Popis souboru: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fbinf.2024.1340339/full; https://doaj.org/toc/2673-7647

Přístupová URL adresa: https://doaj.org/article/961d2c23e9cc4a02a8c14cc9b774b873

Learning a Sparse Generative Non-Parametric Supervised Autoencoder

Autoři: Michel Barlaud Frederic Guyard

Zdroj: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). :3315-3319

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 01 natural sciences, 0105 earth and related environmental sciences

Přístupová URL adresa: https://dblp.uni-trier.de/db/conf/icassp/icassp2021.html#BarlaudG21

A Semi-Supervised Approach to Anomaly Detection for Tax Compliance

Autoři: Leo Corman Jason Bono Catherine Acton a další

Témata: autoencoder, sparse data, deep anomaly detection, ensemble, deep learning, semi-supervised

Přístupová URL adresa: https://zenodo.org/records/14009896

Intelligent evaluation method for identifying favorable shale oil areas based on improved stacked sparse autoencoder.

Autoři: Rui Xu Tie Yan Shihui Sun a další

Zdroj: Oil Shale. 2025, Vol. 42 Issue 1, p79-114. 36p.

Témata: *PETROLEUM prospecting, SHALE oils, SUPERVISED learning, AUTOENCODERS, MACHINE learning

Demography-based facial retouching detection using subclass supervised sparse autoencoder

Autoři: Aparna Bharati Richa Singh Kevin W. Bowyer a další

Zdroj: 2017 IEEE International Joint Conference on Biometrics (IJCB). :474-482

Témata: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 10. No inequality

Přístupová URL adresa: http://arxiv.org/pdf/1709.07598
http://arxiv.org/abs/1709.07598
https://arxiv.org/abs/1709.07598
https://dblp.uni-trier.de/db/journals/corr/corr1709.html#abs-1709-07598
https://research.iitj.ac.in/publication/demography-based-facial-retouching-detection-using-subclass
https://ui.adsabs.harvard.edu/abs/2017arXiv170907598B/abstract
https://doi.org/10.1109/BTAS.2017.8272732

Exploring Semi-Supervised Autoencoders: An Approach to Classify Psychotic Disorders through Proteomic Imbalanced Data

Explorando Autoencoders Semi-Supervisionados: Uma Abordagem para Classificar Distúrbios Psicóticos através de Dados Proteómicos não Balenceados

Autoři: Ribeiro, Mariana Montenegro

Témata: Psychotic Disorders, Semi-supervised Autoencoder, Deep Learning, Proteomic Data, Mass Spectrometry, Perturbações Psicóticas, Autoencoder Semi-supervisionado, Dados Proteómicos, Espectrometria de Massa

Dostupnost: https://hdl.handle.net/10316/117998

Sparse Autoencoder Based Semi-Supervised Learning for Phone Classification with Limited Annotations

Autoři: Kumar Dhaka, Akash Salvi, Giampiero

Zdroj: Grounding Language Understanding.

Popis souboru: electronic

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-211654
https://doi.org/10.21437/GLU.2017-5

Demography-based Facial Retouching Detection using Subclass Supervised Sparse Autoencoder

Autoři: Bharati, Aparna Vatsa, Mayank Singh, Richa a další

Témata: Computer Science - Computer Vision and Pattern Recognition, text

URL: http://arxiv.org/abs/1709.07598

Autoencoders for semi-supervised water level modeling in sewer pipes with sparse labeled data

Autoři: Universitat Politècnica de Catalunya. Doctorat en Automàtica, Robòtica i Visió Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial Barcelona Supercomputing Center a další

Témata: Àrees temàtiques de la UPC::Informàtica::Robòtica, Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic, Supervised learning (Machine learning), Water-pipes, Self-supervised, Semi-supervised, Supervised, Autoencoders and latent space, Sparse data, Data distribution, Water, Aprenentatge supervisat (Aprenentatge automàtic), Aigua -- Canonades, Article

URL: https://hdl.handle.net/2117/363386
https://www.mdpi.com/2073-4441/14/3/333
https://www.mdpi.com/2073-4441/14/3/333

AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders

Autoři: Wu, Zhengxuan Arora, Aryaman Geiger, Atticus a další

Témata: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, I.2.7, text

URL: http://arxiv.org/abs/2501.17148

Self-Supervised Learning on Event Camera Data Using Masked Autoencoders

Autoři: Norrby, Emma

Témata: Self-Supervised Learning, Masked Autoencoders, Vision Transformers, Event Camera, Action Recognition, Transfer Learning, Computer Vision and Learning Systems, Datorseende och lärande system, Student thesis, info:eu-repo/semantics/bachelorThesis, text

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-214776

Non-Line-of-Sight Multipath Classification Method for BDS Using Convolutional Sparse Autoencoder with LSTM

Autoři: Qin, Yahang Li, Zhenni Xie, Shengli a další

Témata: Satellites, Long short term memory, Convolution, Solid modeling, Three-dimensional displays, Interference, Urban areas, Convolutional sparse autoencoder, BeiDou Navigation Satellite System (BDS), Long short-term memory (LSTM), Multipath classification, Article

URL: http://repository.hkust.edu.hk/ir/Record/1783.1-144745
https://doi.org/10.26599/TST.2024.9010004
http://lbdiscover.ust.hk/uresolver?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rfr_id=info:sid/HKUST:SPI&rft.genre=article&rft.issn=1007-0214&rft.volume=30&rft.issue=1&rft.date=2025&rft.spage=68&rft.aulast=Qin&rft.aufirst=Yahang&rft.atitle=Non-Line-of-Sight+Multipath+Classification+Method+for+BDS+Using+Convolutional+Sparse+Autoencoder+with+LSTM&rft.title=TSINGHUA+SCIENCE+AND+TECHNOLOGY
http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=LinksAMR&SrcApp=PARTNER_APP&DestLinkType=FullRecord&DestApp=WOS&KeyUT=001314325700004

Augmenting Variational Autoencoders with Sparse Labels: A Unified Framework for Unsupervised, Semi-(un)supervised, and Supervised Learning

Autoři: Berkhahn, Felix Keys, Richard Ouertani, Wajih a další

Témata: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Neural and Evolutionary Computing, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/1908.03015

Stacked semi-supervised autoencoder-regularized RVFLNs for reliable prediction of molten iron quality in blast furnace.

Autoři: Zhou, Ping Zhao, Peng Ou, Zihui a další

Zdroj: Neural Computing & Applications. Jun2025, Vol. 37 Issue 17, p10425-10438. 14p.

Témata: *BLAST furnaces, *FEATURE extraction, *ARTIFICIAL neural networks, *MACHINE learning, *MATHEMATICAL regularization, *LIQUID iron

Towards Principled Evaluations of Sparse Autoencoders for Interpretability and Control

Autoři: Makelov, Aleksandar Lange, George Nanda, Neel

Témata: Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2405.08366

Semi-Supervised Learning with Sparse Autoencoders in Automatic Speech Recognition

Additional Titles: Semi-övervakad inlärning med glesa autoencoders i automatisk taligenkänning

Autoři: DHAKA, AKASH KUMAR

Témata: machine learning, automatic speech recognition, semi supervised learning, Computer Sciences, Datavetenskap (datalogi), Student thesis, info:eu-repo/semantics/bachelorThesis, text

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-197628
EES Examensarbete / Master Thesis

Masked Autoencoder for Self-Supervised Pre-Training on Lidar Point Clouds

Autoři: Hess, Georg Jaxing, Johan Svensson, Elias a další

Zdroj: IEEE Workshop on Applications of Computer Vision (WACV), Waikoloa, USA Proceedings - 2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2023. :350-359

Témata: 3d object detection, Self-supervised, Object detection, Voxel-MAE, Deep learning, Masked autoencoding

Popis souboru: electronic

Přístupová URL adresa: https://research.chalmers.se/publication/536005
https://research.chalmers.se/publication/535108
https://openaccess.thecvf.com/content/WACV2023W/Pretrain/papers/Hess_Masked_Autoencoder_for_Self-Supervised_Pre-Training_on_Lidar_Point_Clouds_WACVW_2023_paper.pdf

Semi-supervised Learning with Sparse Autoencoders in Phone Classification

Autoři: Dhaka, Akash Kumar Salvi, Giampiero

Témata: Statistics - Machine Learning, Computer Science - Computation and Language, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/1610.00520

Learning biologically relevant features in a pathology foundation model using sparse autoencoders

Autoři: Le, Nhat Minh Shen, Ciyue Patel, Neel a další

Témata: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, text

URL: http://arxiv.org/abs/2407.10785