Deep learning for music generation: challenges and directions
Sign Up to like & getrecommendations! Published in 2020 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3813-6
Abstract: In addition to traditional tasks such as prediction, classification and translation, deep learning is receiving growing attention as an approach for music generation, as witnessed by recent research groups such as Magenta at Google and… read more here.
Keywords: music generation; music; learning architectures; learning music ... See more keywords
Deep Learning Architectures for Accurate Millimeter Wave Positioning in 5G
Sign Up to like & getrecommendations! Published in 2019 at "Neural Processing Letters"
DOI: 10.1007/s11063-019-10073-1
Abstract: The introduction of 5G’s millimeter wave transmissions brings a new paradigm to wireless communications. Whereas physical obstacles were mostly associated with signal attenuation, their presence now adds complex, non-linear phenomena, including reflections and scattering. The… read more here.
Keywords: architectures accurate; millimeter; learning architectures; deep learning ... See more keywords
Predicting apparent personality from body language: benchmarking deep learning architectures for adaptive social human–robot interaction
Sign Up to like & getrecommendations! Published in 2021 at "Advanced Robotics"
DOI: 10.1080/01691864.2021.1974941
Abstract: First impressions of personality traits can be inferred by non-verbal behaviours such as head pose, body postures, and hand gestures. Enabling social robots to infer the apparent personalities of their users based on such non-verbal… read more here.
Keywords: personality traits; learning architectures; deep learning; personality ... See more keywords
Comprehensive evaluation of deep learning architectures for prediction of DNA/RNA sequence binding specificities
Sign Up to like & getrecommendations! Published in 2019 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btz339
Abstract: Abstract Motivation Deep learning architectures have recently demonstrated their power in predicting DNA- and RNA-binding specificity. Existing methods fall into three classes: Some are based on convolutional neural networks (CNNs), others use recurrent neural networks… read more here.
Keywords: learning architectures; dna rna; deep learning; comprehensive evaluation ... See more keywords
Quantum Entanglement in Deep Learning Architectures.
Sign Up to like & getrecommendations! Published in 2019 at "Physical review letters"
DOI: 10.1103/physrevlett.122.065301
Abstract: Modern deep learning has enabled unprecedented achievements in various domains. Nonetheless, employment of machine learning for wave function representations is focused on more traditional architectures such as restricted Boltzmann machines (RBMs) and fully connected neural… read more here.
Keywords: entanglement deep; learning; deep learning; learning architectures ... See more keywords
A Survey of Deep Learning Architectures for Privacy-Preserving Machine Learning With Fully Homomorphic Encryption
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3219049
Abstract: Outsourced computation for neural networks allows users access to state-of-the-art models without investing in specialized hardware and know-how. The problem is that the users lose control over potentially privacy-sensitive data. With homomorphic encryption (HE), a… read more here.
Keywords: homomorphic encryption; privacy preserving; learning architectures; deep learning ... See more keywords
Deep learning architectures for multi-label classification of intelligent health risk prediction
Sign Up to like & getrecommendations! Published in 2017 at "BMC Bioinformatics"
DOI: 10.1186/s12859-017-1898-z
Abstract: BackgroundMulti-label classification of data remains to be a challenging problem. Because of the complexity of the data, it is sometimes difficult to infer information about classes that are not mutually exclusive. For medical data, patients… read more here.
Keywords: classification; learning; learning architectures; multi label ... See more keywords
Post Hoc Sample Size Estimation for Deep Learning Architectures for ECG-Classification.
Sign Up to like & getrecommendations! Published in 2023 at "Studies in health technology and informatics"
DOI: 10.3233/shti230099
Abstract: Deep Learning architectures for time series require a large number of training samples, however traditional sample size estimation for sufficient model performance is not applicable for machine learning, especially in the field of electrocardiograms (ECGs).… read more here.
Keywords: sample size; learning architectures; deep learning; size estimation ... See more keywords