Results 71 to 80 of about 119,888 (330)
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
doaj +1 more source
The Optimally Designed Deep Autoencoder-Based Compressive Sensing Framework for 1D and 2D Signals
IEEE AccessThe capacity of Compressive Sensing (CS) to recreate original data from a limited number of samples has led to a surge in attention in recent years.
Irfan Ahmed +3 more
doaj +1 more source
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
doaj +1 more source
Semisupervised Autoencoder for Sentiment Analysis
, 2015 In this paper, we investigate the usage of autoencoders in modeling textual data. Traditional autoencoders suffer from at least two aspects: scalability with the high dimensionality of vocabulary size and dealing with task-irrelevant words.
Zhai, Shuangfei, Zhang, Zhongfei
core +1 more source
, 2020 Learning the true density in high-dimensional feature spaces is a well-known problem in machine learning. In this work, we consider generative autoencoders based on maximum-mean discrepancy (MMD) and provide theoretical insights. In particular, (i) we prove that MMD coupled with Coulomb kernels has optimal convergence properties, which are similar to ...
Emanuele Sansone +2 more
openaire +2 more sources
Multiresolution convolutional autoencoders
Journal of Computational Physics, 2023 20 pages, 11 ...
Yuying Liu +3 more
openaire +2 more sources
Unsupervised Deep Learning for Structural Health Monitoring
Big Data and Cognitive Computing, 2023 In the last few decades, structural health monitoring has gained relevance in the context of civil engineering, and much effort has been made to automate the process of data acquisition and analysis through the use of data-driven methods.
Roberto Boccagna +4 more
doaj +1 more source
Feature Extraction from Building Submetering Networks Using Deep Learning
Sensors, 2020 The understanding of the nature and structure of energy use in large buildings is vital for defining novel energy and climate change strategies. The advances on metering technology and low-cost devices make it possible to form a submetering network ...
Antonio Morán +5 more
doaj +1 more source
SAFEPA: An Expandable Multi-Pose Facial Expressions Pain Assessment Method
Applied Sciences, 2023 Accurately assessing the intensity of pain from facial expressions captured in videos is crucial for effective pain management and critical for a wide range of healthcare applications.
Thoria Alghamdi, Gita Alaghband
doaj +1 more source
Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites
Advanced Functional Materials, EarlyView.A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou +5 more
wiley +1 more source