Search Results - Neural generative autoencoder

A neural generative autoencoder for bilingual word embeddings by Su, Jinsong, Wu, Shan, Zhang, Biao, Wu, Changxing, Qin, Yue, Xiong, Deyi

“… Instead, in this paper, we propose a neural generative bilingual autoencoder (NGBAE) which introduces a latent variable to explicitly induce the underlying semantics of bilingual text…”
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Convolutional Graph Autoencoder: A Generative Deep Neural Network for Probabilistic Spatio-Temporal Solar Irradiance Forecasting by Khodayar, Mahdi, Mohammadi, Saeed, Khodayar, Mohammad E., Wang, Jianhui, Liu, Guangyi

“… In this paper, a deep generative model is introduced to capture continuous probability densities corresponding to the nodes of an arbitrary graph…”
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De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping by Sattarov, Boris, Baskin, Igor I, Horvath, Dragos, Marcou, Gilles, Bjerrum, Esben Jannik, Varnek, Alexandre

“…Here we show that Generative Topographic Mapping (GTM) can be used to explore the latent space of the SMILES-based autoencoders and generate focused molecular libraries of interest…”
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Resolution-robust Large Mask Inpainting with Fourier Convolutions by Suvorov, Roman, Logacheva, Elizaveta, Mashikhin, Anton, Remizova, Anastasia, Ashukha, Arsenii, Silvestrov, Aleksei, Kong, Naejin, Goka, Harshith, Park, Kiwoong, Lempitsky, Victor

“…Modern image inpainting systems, despite the significant progress, often struggle with large missing areas, complex geometric structures, and high-resolution…”
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Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes by Hahner, Sara, Garcke, Jochen

“…The analysis of deforming 3D surface meshes is accelerated by autoencoders since the low-dimensional embeddings can be used to visualize underlying dynamics…”
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FaceTuneGAN: Face autoencoder for convolutional expression transfer using neural generative adversarial networks by Olivier, Nicolas, Baert, Kelian, Danieau, Fabien, Multon, Franck, Avril, Quentin

“… Leveraging recently released large face scan databases (FaceScape and CoMA), a neural network has been trained to decouple factors of variations with a better knowledge…”
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3D-Convolutional Neural Network with Generative Adversarial Network and Autoencoder for Robust Anomaly Detection in Video Surveillance by Shin, Wonsup, Bu, Seok-Jun, Cho, Sung-Bae

“… We propose a hybrid deep learning model composed of a video feature extractor trained by generative adversarial network with deficient anomaly data and an anomaly detector boosted by transferring the extractor…”
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Improved Prediction of Aquatic Beetle Diversity in a Stagnant Pool by a One-Dimensional Convolutional Neural Network Using Variational Autoencoder Generative Adversarial Network-Generated Data by Hu, Miao, Jiang, Shujiao, Jia, Fenglong, Yang, Xiaomei, Li, Zhiqiang

“… Expanding limited experimental data using a variational autoencoder generative adversarial network (VAEGAN…”
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MIDI-based generative neural networks with variational autoencoders for innovative music creation by Rosalina, Rosalina, Sahuri, Genta

“…)-based generative neural networks (GNNs), this study explores the field of creative music composition…”
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Generative Adversarial Attack on Ensemble Clustering by Kumar, Chetan, Kumar, Deepak, Shao, Ming

“…Adversarial attack on learning tasks has attracted substantial attention in recent years; however, most existing works focus on supervised learning. Recently,…”
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Information Bottlenecked Variational Autoencoder for Disentangled 3D Facial Expression Modelling by Sun, Hao, Pears, Nick, Gu, Yajie

“… We propose a novel variational autoencoder (VAE) framework to disentangle identity and expression from 3D input faces that have a wide variety of expressions…”
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Generative chemistry: drug discovery with deep learning generative models by Bian, Yuemin, Xie, Xiang-Qun

“…The de novo design of molecular structures using deep learning generative models introduces an encouraging solution to drug discovery in the face of the continuously increased cost of new drug development…”
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Network intrusion detection based on conditional wasserstein variational autoencoder with generative adversarial network and one-dimensional convolutional neural networks by He, Jiaxing, Wang, Xiaodan, Song, Yafei, Xiang, Qian, Chen, Chen

“… We propose Conditional Wasserstein Variational Autoencoders with Generative Adversarial Network (CWVAEGAN…”
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Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals by Dash, Saloni, Balasubramanian, Vineeth N, Sharma, Amit

“…Counterfactual examples for an input-perturbations that change specific features but not others-have been shown to be useful for evaluating bias of machine…”
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Lifelong Generative Adversarial Autoencoder by Ye, Fei, Bors, Adrian G.

“… during a certain period of time. However, modern neural networks suffer from degenerated performance when learning multiple domains sequentially and fail to recognize past learned tasks after being retrained…”
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Reconstructing feedback representations in the ventral visual pathway with a generative adversarial autoencoder by Al-Tahan, Haider, Mohsenzadeh, Yalda

“… the computational role of feedback processes poorly understood. Here, we developed a generative autoencoder neural network model and adversarially trained it on a categorically diverse data set of images…”
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C-VTON: Context-Driven Image-Based Virtual Try-On Network by Fele, Benjamin, Lampe, Ajda, Peer, Peter, Struc, Vitomir

“…Image-based virtual try-on techniques have shown great promise for enhancing the user-experience and improving customer satisfaction on fashion-oriented…”
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Generative Adversarial Graph Convolutional Networks for Human Action Synthesis by Degardin, Bruno, Neves, Joao, Lopes, Vasco, Brito, Joao, Yaghoubi, Ehsan, Proenca, Hugo

“… the benefits of Generative Adversarial Networks and Graph Convolutional Networks to synthesise the kinetics of the human body…”
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BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detection by Jeong, Yonghyun, Kim, Doyeon, Min, Seungjai, Joe, Seongho, Gwon, Youngjune, Choi, Jongwon

“…The advancement in numerous generative models has a two-fold effect: a simple and easy generation of realistic synthesized images, but also an increased risk of malicious abuse of those images…”
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Adversarial Open Domain Adaptation for Sketch-to-Photo Synthesis by Xiang, Xiaoyu, Liu, Ding, Yang, Xiao, Zhu, Yiheng, Shen, Xiaohui, Allebach, Jan P.

“…In this paper, we explore open-domain sketch-to-photo translation, which aims to synthesize a realistic photo from a freehand sketch with its class label, even…”
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