Search Results - Conditional Variational Autoencoder~

KilonovaNet: Surrogate models of kilonova spectra with conditional variational autoencoders by Lukošiute, K, Raaijmakers, G, Doctor, Z, Soares-Santos, M, Nord, B

“… In this work, we present kilonovanet, an implementation of conditional variational autoencoders (cVAEs…”
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A balanced mineral prospectivity model of Canadian magmatic Ni (± Cu ± Co ± PGE) sulphide mineral systems using conditional variational autoencoders by Nagasingha, Lahiru M.A., Bérubé, Charles L., Lawley, Christopher J.M.

“… We address the data imbalance challenge in MPM by proposing a novel generative modelling approach using a conditional variational autoencoder (CVAE…”
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Analysis of Training and Seed Bias in Small Molecules Generated with a Conditional Graph-Based Variational Autoencoder─Insights for Practical AI-Driven Molecule Generation by Kang, Seung-Gu, Morrone, Joseph A, Weber, Jeffrey K, Cornell, Wendy D

“… In this work, we analyze the impact of seed and training bias on the output of an activity-conditioned graph-based variational autoencoder (VAE…”
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Predicting Potent Compounds Using a Conditional Variational Autoencoder Based upon a New Structure–Potency Fingerprint by Janela, Tiago, Takeuchi, Kosuke, Bajorath, Jürgen

“… This encoding enables the derivation of a conditional variational autoencoder (CVAE) using SPFPs of training compounds and apply the model to predict the SPFP potency module of test compounds using only their structure module as input. The SPFP…”
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Normative Modeling Via Conditional Variational Autoencoder and Adversarial Learning to Identify Brain Dysfunction in Alzheimer's Disease by Wang, Xuetong, Zhou, Rong, Zhao, Kanhao, Leow, Alex, Zhang, Yu, He, Lifang

“… In this study, we propose a novel normative modeling method by combining conditional variational autoencoder with adversarial learning (ACVAE…”
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Cybersecurity enhancement using conditional generative adversarial network with transformer-based conditional variational autoencoder by Singh, Prithvipal, Singh, Sandeep, Singh, Gurupdesh, Singh, Amritpal

“…Since, Artificial Intelligence is highly developing and concatenating into several domains, cybersecurity is an important field of delivering both the…”
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AEGANAuth: Autoencoder GAN-Based Continuous Authentication With Conditional Variational Autoencoder Generative Adversarial Network by Li, Yantao, Ouyang, Caike, Huang, Hongyu

“… In this article, we present AEGANAuth, a lightweight and effective autoencoder GAN (AEGAN)-based continuous Authentication system for mobile devices using conditional variational autoencoder generative adversarial network (CVAEGAN…”
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Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT by Lopez-Martin, Manuel, Carro, Belen, Sanchez-Esguevillas, Antonio, Lloret, Jaime

“…The purpose of a Network Intrusion Detection System is to detect intrusive, malicious activities or policy violations in a host or host’s network. In current…”
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Improving the Classification Effectiveness of Intrusion Detection by Using Improved Conditional Variational AutoEncoder and Deep Neural Network by Yang, Yanqing, Zheng, Kangfeng, Wu, Chunhua, Yang, Yixian

“… We propose a novel intrusion detection model that combines an improved conditional variational AutoEncoder (ICVAE…”
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Molecular generative model based on conditional variational autoencoder for de novo molecular design by Lim, Jaechang, Ryu, Seongok, Kim, Jin Woo, Kim, Woo Youn

“…We propose a molecular generative model based on the conditional variational autoencoder for de novo molecular design…”
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Generating multivariate load states using a conditional variational autoencoder by Wang, Chenguang, Sharifnia, Ensieh, Gao, Zhi, Tindemans, Simon H., Palensky, Peter

“… In this paper, a multivariate load state generating model on the basis of a conditional variational autoencoder (CVAE…”
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Learning conditional variational autoencoders with missing covariates by Ramchandran, Siddharth, Tikhonov, Gleb, Lönnroth, Otto, Tiikkainen, Pekka, Lähdesmäki, Harri

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MGCVAE: Multi-Objective Inverse Design via Molecular Graph Conditional Variational Autoencoder by Lee, Myeonghun, Min, Kyoungmin

“… The performance of the molecular graph conditional variational autoencoder (MGCVAE) for generating molecules with specific desired properties was investigated by comparing it to a molecular graph variational autoencoder (MGVAE…”
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Data-driven design exploration method using conditional variational autoencoder for airfoil design by Yonekura, Kazuo, Suzuki, Katsuyuki

“… In the present work, we achieve this goal using a conditional variational autoencoder (CVAE). The method enables us to analyze the relationship between aerodynamic performance and the shape of aerodynamic parts, and to explore new designs for the parts…”
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Power Plant Model Parameter Calibration Using Conditional Variational Autoencoder by Khazeiynasab, Seyyed Rashid, Zhao, Junbo, Batarseh, Issa, Tan, Bendong

“… Then, synchrophasor measurement-based conditional variational autoencoder is developed to estimate the parameters' posterior distributions even in the presence of a high-dimensional case…”
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Bayesian parameter estimation using conditional variational autoencoders for gravitational-wave astronomy by Gabbard, Hunter, Messenger, Chris, Heng, Ik Siong, Tonolini, Francesco, Murray-Smith, Roderick

“… min on a limited range of key source parameters. Here, we show that a conditional variational autoencoder pretrained on binary black hole signals can return Bayesian…”
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Toward Effective Intrusion Detection Using Log-Cosh Conditional Variational Autoencoder by Xu, Xing, Li, Jie, Yang, Yang, Shen, Fumin

“… To tackle this problem, in this article, we propose a novel deep learning-based intrusion detection method named log-cosh conditional variational autoencoder (LCVAE…”
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Sensing anomaly of photovoltaic systems with sequential conditional variational autoencoder by Li, Ding, Zhang, Yufei, Yang, Zheng, Jin, Yaohui, Xu, Yanyan

“… This study proposes the Sequential Conditional Variational Autoencoder (SCVAE), which can cope with the sequential impacts of the environment on PV…”
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Rapid Generation of Kilonova Light Curves Using Conditional Variational Autoencoder by Saha, Surojit, Williams, Michael J., Datrier, Laurence, Hayes, Fergus, Nicholl, Matt, Kong, Albert K. H., Hendry, Martin, Heng, IK Siong, Lamb, Gavin P., Lin, En-Tzu, Williams, Daniel

“…The discovery of the optical counterpart, along with the gravitational waves (GWs) from GW170817, of the first binary neutron star merger has opened up a new…”
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Semi-Supervised Deep Conditional Variational Autoencoder for Soft Sensor Modeling by Tang, Xiaochu, Yan, Jiawei, Li, Yuan, Zhang, Xinmin, Song, Zhihuan

“…Variational autoencoder (VAE) as an unsupervised deep generated model has been widely applied to process modeling for industrial processes due to its excellent ability in nonlinear and uncertain feature extraction…”
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