Variational Autoencoder for End-to-End Control of Autonomous Driving with Novelty Detection and Training De-biasing by Amini, Alexander, Araki, Brandon, Rus, Daniela, Schwarting, Wilko, Rosman, Guy, Karaman, Sertac, Rus, Daniela L

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Disentangling latent space of variational autoencoder with distribution dependent guarantees for out-of-distribution detection and reasoning by Rahiminasab Zahra Reza (Zahra Rahiminasab)

“…As a result, in our first attempt, we create an ensemble of β-Variational autoencoders (EBVAE) as OOD detectors that can be trained with multi-label data. …”
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Generating subpopulation-specific biventricular anatomy models using conditional point cloud variational autoencoders by Beetz, M, Banerjee, A, Grau, V

“…In this work, we propose a novel geometric deep learning method based on the variational autoencoder (VAE) framework capable of accurately encoding, reconstructing, and synthesizing 3D surface models of the biventricular anatomy. …”

Generative Deep Learning Techniques for Traffic Matrix Estimation From Link Load Measurements by Grigorios Kakkavas, Nikolaos Fryganiotis, Vasileios Karyotis, Symeon Papavassiliou

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Learning Latent Representation of Freeway Traffic Situations from Occupancy Grid Pictures Using Variational Autoencoder by Olivér Rákos, Tamás Bécsi, Szilárd Aradi, Péter Gáspár

Subjects: “…convolutional variational autoencoder…”
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ViV-Ano: Anomaly Detection and Localization Combining Vision Transformer and Variational Autoencoder in the Manufacturing Process by Byeonggeun Choi, Jongpil Jeong

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Towards an Effective Intrusion Detection Model Using Focal Loss Variational Autoencoder for Internet of Things (IoT) by Shapla Khanam, Ismail Ahmedy, Mohd Yamani Idna Idris, Mohamed Hisham Jaward

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Malware detection framework based on graph variational autoencoder extracted embeddings from API-call graphs by Hakan Gunduz

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Desertification Detection Using an Improved Variational Autoencoder-Based Approach Through ETM-Landsat Satellite Data by Yacine Zerrouki, Fouzi Harrou, Nabil Zerrouki, Abdelkader Dairi, Ying Sun

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Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders by Maxim Ziatdinov, Chun Yin (Tommy) Wong, Sergei V Kalinin

Subjects: “…variational autoencoder…”
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Variational autoencoder analysis gas sensor array on the preservation process of contaminated mussel shells (Mytilus edulis) by Cendra Devayana Putra, Achmad Ilham Fanany Al Isyrofie, Suryani Dyah Astuti, Berliana Devianti Putri, Dyah Rohmatul Ummah, Miratul Khasanah, Perwira Annissa Dyah Permatasari, Ardiyansyah Syahrom

“…PCA can keep an average of 33% nearest data in the same neighbourhood. While variational autoencoder can keep 14% nearest data in the same neighbour, and autoencoder can keep 8% nearest data in the same area.…”
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Learning Subject-Generalized Topographical EEG Embeddings Using Deep Variational Autoencoders and Domain-Adversarial Regularization by Juan Lorenzo Hagad, Tsukasa Kimura, Ken-ichi Fukui, Masayuki Numao

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Advances Toward the Next Generation Fire Detection: Deep LSTM Variational Autoencoder for Improved Sensitivity and Reliability by Zhaoyi Xu, Yanjie Guo, Joseph Homer Saleh

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UNSUPERVISED PROBABILISTIC ANOMALY DETECTION OVER NOMINAL SUBSYSTEM EVENTS THROUGH A HIERARCHICAL VARIATIONAL AUTOENCODER by Alexandre Trilla, Nenad Mijatovic, Xavier Vilasis-Cardona

“…Secondly, it generalizes the learned embedded regularity of a Variational Autoencoder manifold by merging latent space-overlapping deviations with non-overlapping synthetic irregularities. …”

Leveraging Dual Variational Autoencoders and Generative Adversarial Networks for Enhanced Multimodal Interaction in Zero-Shot Learning by Ning Li, Jie Chen, Nanxin Fu, Wenzhuo Xiao, Tianrun Ye, Chunming Gao, Ping Zhang

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Machinery New Emerge Fault Diagnosis Based on Deep Convolution Variational Autoencoder and Adaptive Label Propagation by Bo She, Xuan Wang

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Early Detection and Diagnosis of Wind Turbine Abnormal Conditions Using an Interpretable Supervised Variational Autoencoder Model by Adaiton Oliveira-Filho, Ryad Zemouri, Philippe Cambron, Antoine Tahan

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Predicting NOx Distribution in a Micro Rich–Quench–Lean Combustor Using a Variational Autoencoder by Peiliang Yan, Weijun Fan, Rongchun Zhang

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A multi-encoder variational autoencoder controls multiple transformational features in single-cell image analysis by Luke Ternes, Mark Dane, Sean Gross, Marilyne Labrie, Gordon Mills, Joe Gray, Laura Heiser, Young Hwan Chang

“…The Multi-Encoder Variational AutoEncoder (ME-VAE) is a computational model that can control for multiple transformational features in single-cell imaging data, enabling researchers to extract meaningful single-cell information and better separate heterogeneous cell types.…”
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COLORIZING SENTINEL-1 SAR IMAGES USING A VARIATIONAL AUTOENCODER CONDITIONED ON SENTINEL-2 IMAGERY by M. Schmitt, L. H. Hughes, M. Körner, X. X. Zhu, X. X. Zhu

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