Joint Chord and Key Estimation Based on a Hierarchical Variational Autoencoder with Multi-task Learning by Yiming Wu, Kazuyoshi Yoshii

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Embedded Generative Air Pollution Model with Variational Autoencoder and Environmental Factor Effect in Ulaanbaatar City by Bulgansaikhan Baldorj, Munkherdene Tsagaan, Lodoysamba Sereeter, Amanjol Bulkhbai

“…To obtain preliminary pollution information with regard to environmental factors, we developed a variational autoencoder and feedforward neural network-based embedded generative model to examine the relationship between air quality and the effects of environmental factors. …”
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3D landmark‐based face restoration for recognition using variational autoencoder and triplet loss by Sahil Sharma, Vijay Kumar

“…It utilizes the concept of deep features from variational autoencoders. Further, these deep feature embeddings are trained using triplet loss training to increase the distance between embeddings of different persons and decreasing the distance between embeddings of the same person. …”
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A Multi-Scale Electricity Consumption Prediction Algorithm Based on Time-Frequency Variational Autoencoder by Kaihong Zheng, Peng Li, Shangli Zhou, Wenhan Zhang, Sheng Li, Lukun Zeng, Yingnan Zhang

Subjects: “…Time-frequency variational autoencoder…”
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Deep clustering of small molecules at large-scale via variational autoencoder embedding and K-means by Hamid Hadipour, Chengyou Liu, Rebecca Davis, Silvia T. Cardona, Pingzhao Hu

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VASC: Dimension Reduction and Visualization of Single-cell RNA-seq Data by Deep Variational Autoencoder by Dongfang Wang, Jin Gu

“…Keywords: Single cell RNA sequencing, Deep variational autoencoder, Dimension reduction, Visualization, Dropout…”
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Data Augmentation with Cross-Modal Variational Autoencoders (<tt>DACMVA</tt>) for Cancer Survival Prediction by Sara Rajaram, Cassie S. Mitchell

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Variational Autoencoder for Classification and Regression for Out-of-Distribution Detection in Learning-Enabled Cyber-Physical Systems by Feiyang Cai, Ali I. Ozdagli, Xenofon Koutsoukos

“…The proposed approach incorporates the variational autoencoder for classification and regression model to the Inductive Conformal Anomaly Detection (ICAD) framework, enabling the detection algorithm to take into consideration not only the LEC inputs but also the LEC outputs. …”
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GeoSDVA: A Semi-Supervised Dirichlet Variational Autoencoder Model for Transportation Mode Identification by Xiaoxi Zhang, Yuan Gao, Xin Wang, Jun Feng, Yan Shi

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BindVAE: Dirichlet variational autoencoders for de novo motif discovery from accessible chromatin by Meghana Kshirsagar, Han Yuan, Juan Lavista Ferres, Christina Leslie

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Non-Parallel Whisper-to-Normal Speaking Style Conversion Using Auxiliary Classifier Variational Autoencoder by Shogo Seki, Hirokazu Kameoka, Takuhiro Kaneko, Kou Tanaka

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Toward a more informative representation of the fetal–neonatal brain connectome using variational autoencoder by Jung-Hoon Kim, Josepheen De Asis-Cruz, Dhineshvikram Krishnamurthy, Catherine Limperopoulos

“…To obtain a nuanced understanding of fetal–neonatal brain development, including nonlinear growth, for the first time, we developed quantitative, systems-wide representations of brain activity in a large sample (&gt;500) of fetuses, preterm, and full-term neonates using an unsupervised deep generative model called variational autoencoder (VAE), a model previously shown to be superior to linear models in representing complex resting-state data in healthy adults. …”
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Automated Discovery of Anomalous Features in Ultralarge Planetary Remote-Sensing Datasets Using Variational Autoencoders by Adam Lesnikowski, Valentin Tertius Bickel, Daniel Angerhausen

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Generating Polyphonic Symbolic Emotional Music in the Style of Bach Using Convolutional Conditional Variational Autoencoder by Jacek Grekow

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MC-RVAE: Multi-channel recurrent variational autoencoder for multimodal Alzheimer’s disease progression modelling by Gerard Martí-Juan, Marco Lorenzi, Gemma Piella

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Variational autoencoder-based chemical latent space for large molecular structures with 3D complexity by Toshiki Ochiai, Tensei Inukai, Manato Akiyama, Kairi Furui, Masahito Ohue, Nobuaki Matsumori, Shinsuke Inuki, Motonari Uesugi, Toshiaki Sunazuka, Kazuya Kikuchi, Hideaki Kakeya, Yasubumi Sakakibara

“…In this study, we developed a deep-learning method, called NP-VAE (Natural Product-oriented Variational Autoencoder), based on variational autoencoder for managing hard-to-analyze datasets from DrugBank and large molecular structures such as natural compounds with chirality, an essential factor in the 3D complexity of compounds. …”
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Holographic-(V)AE: An end-to-end SO(3)-equivariant (variational) autoencoder in Fourier space by Gian Marco Visani, Michael N. Pun, Arman Angaji, Armita Nourmohammad

“…Here, we present holographic-(variational) autoencoder [H-(V)AE], a fully end-to-end SO(3)-equivariant (variational) autoencoder in Fourier space, suitable for unsupervised learning and generation of data distributed around a specified origin in 3D. …”
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Classification of Anomaly Patterns in Integrated Energy Systems Based on Conditional Variational Autoencoder and Attention Mechanism by Wei Guo, Shengbo Sun, Chenkang Tang, Gang Li, Xinlei Bai, Zhenbing Zhao

“…This paper proposes a classification method that employs a conditional variational autoencoder and attention mechanism for deep clustering to identify anomaly patterns and distinguish between normal and anomaly datasets. …”
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Unsupervised Anomaly Video Detection via a Double-Flow ConvLSTM Variational Autoencoder by Lin Wang, Haishu Tan, Fuqiang Zhou, Wangxia Zuo, Pengfei Sun

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Exploration of optimal microstructure and mechanical properties in continuous microstructure space using a variational autoencoder by Yongju Kim, Hyung Keun Park, Jaimyun Jung, Peyman Asghari-Rad, Seungchul Lee, Jin You Kim, Hwan Gyo Jung, Hyoung Seop Kim

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