A generative model for evaluating missing data methods in large epidemiological cohorts by Lav Radosavljević, Stephen M. Smith, Thomas E. Nichols

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Traditional Chinese Medicine Prescription Generation Model Based on Search Enhancement by ZHAO Zijuan, REN Xueting, SONG Kai, QIANG Yan, ZHAO Juanjuan, ZHANG Junlong

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Screening of multi deep learning-based de novo molecular generation models and their application for specific target molecular generation by Yishu Wang, Mengyao Guo, Xiaomin Chen, Dongmei Ai

“…In this study, we modified one top-performing molecular generation model on the basis of the generative pretraining transformer (GPT) architecture in three directions. …”
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Frontal Face Generation Based on Attitude Point Guidance and Attention Mechanism Improvement by Jihui Zhao, Zhengyi Yuan, Junhu Zhang, Haitao Li, Hui Li

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Individualized models of social judgments and context-dependent representations by Daniel N. Albohn, Stefan Uddenberg, Alexander Todorov

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Into the latent space of capacitive sensors: interpolation and synthetic data generation using variational autoencoders by Miguel Monteagudo Honrubia, Francisco Javier Herraiz-Martínez, Javier Matanza Domingo

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Penerapan Deep Convolutional Generative Adversarial Network Untuk Menciptakan Data Sintesis Perilaku Pengemudi Dalam Berkendara by Michael Stephen Lui, Fitra Abdurrachman Bachtiar, Novanto Yudistira

“…One way to increase deep learning method performance is by using additional synthesis data made by generative model. Deep Convolutional Generative Adversarial Network (DCGAN) is a generative model that uses convolution layer. …”
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Pengembangan Auto-AI Model Generatif Analisis Kompleksitas Waktu Algoritma Untuk Data Multi-Sensor IoT Pada Node-RED Menggunakan Extreme Learning Machine by Imam Cholissodin, Dahnial Syauqy, Dwi Ady Firmanda, Ibrahim Aji, Edy Rahman, Syazwandy Harahap, Fernando Septino

“…The steps in the study are utilized to create a generative model based on the Extreme Learning Machine (ELM) algorithm according to the recording of computational time values on several tests to automate the determination of time complexity equation model of the algorithm in general including the search of best cases, worst cases, and average cases for non-recursive, and base cases and recurrent cases for recursive, as well as algorithms that contain both. …”
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Modeling carbon dioxide emissions in power plants: a perspective on smart cities and low-carbon economy by Isa S. Qamber

“…Researchers aim to identify strategies for meeting emission reduction goals by analyzing power generation models. This involves implementing policies and technologies aimed at reducing GHG emissions and mitigating climate change. …”
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IMPLEMENTATION OF LEARNING MANAGEMENT SYSTEMS WITH GENERATIVE ARTIFICIAL INTELLIGENCE FUNCTIONS IN THE POST-PANDEMIC ENVIRONMENT by Denis-Cătălin Arghir

“…The system proposes the integration of a language generation model equipped with Application Programming Interface (API) access. …”
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Inverse design of nanophotonic devices enabled by optimization algorithms and deep learning: recent achievements and future prospects by Kim Junhyeong, Kim Jae-Yong, Kim Jungmin, Hyeong Yun, Neseli Berkay, You Jong-Bum, Shim Joonsup, Shin Jonghwa, Park Hyo-Hoon, Kurt Hamza

“…Furthermore, we explore state-of-the-art deep learning techniques, involving discriminative models, generative models, and reinforcement learning. We also introduce and categorize several notable inverse-designed nanophotonic devices and their respective design methodologies. …”
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PEMBELAJARAN REMEDIAL TERPADU DENGAN MENERAPKAN MODEL PEMBELAJARAN GENERATIF UNTUK MENGUBAH MISKONSEPSI SISWA TERHADAP KONSEP USAHA DAN ENERGI by Nur Rosuli, Irwan Koto, Nyoman Rohadi

“…The result showed that there was a significant effect on remedial learning related to applying generative models to change in students’ conceptions with t hitung > t tabel (16,33 ). …”
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Explanatory LSTM-AE-Based Anomaly Detection for Time Series Data in Marine Transportation by Zhan Wang, Mwamba Kasongo Dahouda, Hyoseong Hwang, Inwhee Joe

“…The LSTM-AE model shows superior performance compared to other data generation models such as GAN and diffusion models, which have accuracy issues and require high computational cost. …”
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