Search Results - "Constrained autoencoder"

Context-Dependent Manifold Learning in Dynamical Systems: A Neuromodulated Constrained Autoencoder Approach

Authors: Adriaens, Jérôme Drion, Guillaume Sacré, Pierre

Source: Symmetry and Geometry in Neural Representations workshop, NeurIPS 2025, San Diego, United States - California [US-CA], Tuesday Dec 2nd through Sunday Dec 7th

Subject Terms: Nonlinear dimensionality reduction, Neuromodulation, Context-dependent learning, Constrained autoencoder, Engineering, computing & technology, Ingénierie, informatique & technologie

Access URL: https://orbi.uliege.be/handle/2268/336469

Phy-ChemNODE: an end-to-end physics-constrained autoencoder-NeuralODE framework for learning stiff chemical kinetics of hydrocarbon fuels

Authors: Tadbhagya Kumar Anuj Kumar Pinaki Pal

Source: Frontiers in Thermal Engineering. 5

Golden Eagle Optimization CONV-LSTM and Non-Negativity-constrained Autoencoder-Deep Learning Optimization

Authors: Hajim, Wesam

Subject Terms: Deep Learning, Golden Eagle Optimization, Non-Negativity-Constrained Autoencoder, Convolutional Long Short-Term Memory, Spatial and Temporal Features, Drug Response Prediction

Golden eagle optimized CONV-LSTM and non-negativity-constrained autoencoder to support spatial and temporal features in cancer drug response prediction

Authors: Wesam Ibrahim Hajim Suhaila Zainudin Kauthar Mohd Daud et al.

Source: PeerJ Computer Science, Vol 10, p e2520 (2024)

Subject Terms: Deep learning, Golden eagle optimization, Convolutional long short-term memory, Non-negativity-constrained autoencoder, Spatial and temporal features, Drug response prediction, Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: https://peerj.com/articles/cs-2520.pdf; https://peerj.com/articles/cs-2520/; https://doaj.org/toc/2376-5992

Access URL: https://doaj.org/article/b59b72f3de2a4dd4836fa038f5eed496

Probability Correlation Learning for Anomaly Detection based on Distribution-Constrained Autoencoder

Authors: Jihua Wu Lei Zhang Cong Liu et al.

Source: 2022 23rd Asia-Pacific Network Operations and Management Symposium (APNOMS). :1-6

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Constrained Autoencoder-Based Pulse Compressed Thermal Wave Imaging for Sub-Surface Defect Detection

Authors: Kirandeep Kaur Ravibabu Mulaveesala Priyanka Mishra

Source: IEEE Sensors Journal. 22:17335-17342

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/document/9344642

Simultaneous and Proportional Wrist Force Intent Estimation Method using Constrained Autoencoder

Authors: Younggeol Cho Pyungkang Kim Kyung-Soo Kim

Source: 2021 21st International Conference on Control, Automation and Systems (ICCAS). :1917-1921

Subject Terms: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Prediction of Head Motion from Speech Waveforms with a Canonical-Correlation-Constrained Autoencoder

Authors: Hiroshi Shimodaira JinHong Lu

Source: Interspeech 2020. :1301-1305

Subject Terms: FOS: Computer and information sciences, Sound (cs.SD), 03 medical and health sciences, Audio and Speech Processing (eess.AS), FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0305 other medical science, Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing

Access URL: http://arxiv.org/pdf/2002.01869
http://arxiv.org/abs/2002.01869
http://dblp.uni-trier.de/db/conf/interspeech/interspeech2020.html#LuS20
https://arxiv.org/abs/2002.01869
http://ui.adsabs.harvard.edu/abs/2020arXiv200201869L/abstract
https://arxiv.org/pdf/2002.01869.pdf
https://dblp.uni-trier.de/db/conf/interspeech/interspeech2020.html#LuS20

Estimating Simultaneous and Proportional Finger Force Intention Based on sEMG Using a Constrained Autoencoder

Authors: Younggeol Cho Pyungkang Kim Kyung-Soo Kim

Source: IEEE Access, Vol 8, Pp 138264-138276 (2020)

Subject Terms: finger intention estimation, 03 medical and health sciences, neural network, 0206 medical engineering, surface electromyogram (sEMG), Autoencoder, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, 0305 other medical science, TK1-9971

Access URL: https://ieeexplore.ieee.org/ielx7/6287639/8948470/09151957.pdf
https://doaj.org/article/41e5d8a0a53b4a5882e4ce9458546e50
https://dblp.uni-trier.de/db/journals/access/access8.html#ChoKK20
https://ieeexplore.ieee.org/document/9151957/

Driver identification based on hidden feature extraction by using adaptive nonnegativity-constrained autoencoder

Authors: Zhongcheng Wu Jie Chen Jun Zhang

Source: Applied Soft Computing. 74:1-9

Subject Terms: 0502 economics and business, 05 social sciences, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Physics-Constrained Autoencoder Neural Network for the Prediction of Key Granule Properties in a Twin-Screw Granulation Process

Source: Computer Aided Chemical Engineering ISBN: 9780323851596

Reconstruct Anomaly to Normal: Adversarially Learned and Latent Vector-Constrained Autoencoder for Time-Series Anomaly Detection

Authors: Chuanyi Liu Chunkai Zhang Xuan Wang et al.

Source: Lecture Notes in Computer Science ISBN: 9783030893620

Access URL: https://arxiv.org/abs/2010.06846
https://arxiv.org/pdf/2010.06846
https://dblp.uni-trier.de/db/journals/corr/corr2010.html#abs-2010-06846
https://link.springer.com/chapter/10.1007/978-3-030-89363-7_39

Subspace clustering using a low-rank constrained autoencoder

Authors: Yuanyuan Chen Lei Zhang Zhang Yi

Source: Information Sciences. 424:27-38

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://dl.acm.org/doi/10.1016/j.ins.2017.09.047
http://www.sciencedirect.com/science/article/pii/S0020025517309659
https://dblp.uni-trier.de/db/journals/isci/isci424.html#ChenZY18
https://www.sciencedirect.com/science/article/pii/S0020025517309659
https://dl.acm.org/citation.cfm?id=3164000
https://doi.org/10.1016/j.ins.2017.09.047

Prediction of head motion from speech waveforms with a canonical-correlation-constrained autoencoder

Authors: Lu, JinHong Shimodaira, Hiroshi

Index Terms: Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Sound, text

URL: http://arxiv.org/abs/2002.01869

Reconstruct Anomaly to Normal: Adversarial Learned and Latent Vector-constrained Autoencoder for Time-series Anomaly Detection

Authors: Zhang, Chunkai Zuo, Wei Wang, Xuan

Index Terms: Computer Science - Machine Learning, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/2010.06846

Phy-ChemNODE : an end-to-end physics-constrained autoencoder-NeuralODE framework for learning stiff chemical kinetics of hydrocarbon fuels.

Authors: Kumar, Tadbhagya Kumar, Anuj Pal, Pinaki

Source: Frontiers in Thermal Engineering; 2025, p1-8, 8p

Subject Terms: CHEMICAL kinetics, AUTOENCODERS, DIMENSIONAL reduction algorithms, CONSERVATION of mass, PREDICTION models, FOSSIL fuels, CONSTRAINTS (Physics), ARTIFICIAL neural networks

Learned Design of a Compressive Hyperspectral Imager for Remote Sensing by a Physics-Constrained Autoencoder

Authors: Yaron Heiser Adrian Stern

Source: Remote Sensing, Vol 14, Iss 15, p 3766 (2022)

Subject Terms: design learning, deep learning, compressive hyperspectral imaging, remote sensing, Science

File Description: electronic resource

Relation: https://www.mdpi.com/2072-4292/14/15/3766; https://doaj.org/toc/2072-4292

Access URL: https://doaj.org/article/83f6efe3ea0f44bfbebe7c2dbf327a15

HTD-SAE: A Signature-constrained Autoencoder for Hyperspectral Target Detection through Large-scale Pre-training

Authors: Wang, Shuai Li, Yunsong Xie, Weiying et al.

Contributors: Wang, Shuai Li, Yunsong Xie, Weiying et al.

Source: IGARSS 2025 - 2025 IEEE International Geoscience and Remote Sensing Symposium ; page 8649-8653

Availability: https://doi.org/10.1109/igarss55030.2025.11243848
http://xplorestaging.ieee.org/ielx8/11242230/11242244/11243848.pdf?arnumber=11243848

Driver identification based on hidden feature extraction by using adaptive nonnegativity-constrained autoencoder.

Authors: Chen, Jie Wu, ZhongCheng Zhang, Jun

Source: Applied Soft Computing. Jan2019, Vol. 74, p1-9. 9p.

Subject Terms: Identification, Automobile drivers, Feature extraction, Deep learning, Random forest algorithms

Golden eagle optimized CONV-LSTM and non-negativity-constrained autoencoder to support spatial and temporal features in cancer drug response prediction.

Authors: Hajim, Wesam Ibrahim Zainudin, Suhaila Daud, Kauthar Mohd et al.

Source: PeerJ Computer Science; Dec2024, p1-36, 36p

Subject Terms: CONVOLUTIONAL neural networks, LONG short-term memory, DEEP learning, GOLDEN eagle, AUTOENCODERS