Results 31 to 40 of about 30,442 (292)
Feedback Recurrent Autoencoder [PDF]
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020 In this work, we propose a new recurrent autoencoder architecture, termed Feedback Recurrent AutoEncoder (FRAE), for online compression of sequential data with temporal dependency. The recurrent structure of FRAE is designed to efficiently extract the redundancy along the time dimension and allows a compact discrete representation of the data to be ...
Yang Yang 0010 +3 more
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, 2023 Football trajectory modeling is a powerful tool for predicting and evaluating the movement of a football and its dynamics. Masked autoencoders are scalable self-supervised learners used for representation learning of partially observable data.
Tor, Sandra
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Self-Net: Lifelong Learning via Continual Self-Modeling
Frontiers in Artificial Intelligence, 2020 Learning a set of tasks over time, also known as continual learning (CL), is one of the most challenging problems in artificial intelligence. While recent approaches achieve some degree of CL in deep neural networks, they either (1) store a new network ...
Jaya Krishna Mandivarapu +2 more
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CoRR, 2019 Proceedings of the 37th International Conference on Machine ...
Michael Moor +3 more
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Structuring Autoencoders [PDF]
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 2019 In this paper we propose Structuring AutoEncoders (SAE). SAEs are neural networks which learn a low dimensional representation of data which are additionally enriched with a desired structure in this low dimensional space. While traditional Autoencoders have proven to structure data naturally they fail to discover semantic structure that is hard to ...
Marco Rudolph +2 more
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CoRR, 2023 The Variational Autoencoder (VAE) is a seminal approach in deep generative modeling with latent variables. Interpreting its reconstruction process as a nonlinear transformation of samples from the latent posterior distribution, we apply the Unscented Transform (UT) -- a well-known distribution approximation used in the Unscented Kalman Filter (UKF ...
Faris Janjos +3 more
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Reconstruction Residuals Based Long-term Voltage Stability Assessment Using Autoencoders
Journal of Modern Power Systems and Clean Energy, 2020 Real-time voltage stability assessment (VSA) has long been an extensively research topic. In recent years, rapidly mounting deep learning methods have pushed online VSA to a new height that large amounts of learning algorithms are applied for VSA from ...
Haosen Yang, Robert C. Qiu, Houjie Tong
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Method of automatic search for the structure and parameters of neural networks for solving information processing problems [PDF]
Известия Саратовского университета. Новая серия: Математика. Механика. Информатика, 2023 Neural networks are actively used in solving various applied problems of data analysis, processing and generation. When using them, one of the difficult stages is the selection of the structure and parameters of neural networks (the number and types of ...
Obukhov, Artem D.
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UMYU Scientifica JournalAutoencoders have developed into neural search networks in recent years, and the majority of machine learning (ML) methods rely on the input properties to produce high-quality models.
Samuel Michael Ogbe +1 more
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