Nonlinear effects of fiscal policy on national saving: Empirical evidence from emerging Asian economies by Duy-Tung Bui

“…Findings – The empirical results show that tax policy and expenditure policy follow the predictions of the overlapping generation model with finite horizon and the Keynesian view. …”
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Evolutionary generative design of supercritical airfoils: an automated approach driven by small data by Kebin Sun, Weituo Wang, Ran Cheng, Yu Liang, Hairun Xie, Jing Wang, Miao Zhang

“…The EvoGD approach is based on the framework of Evolutionary Computation and employs a series of sophisticated data-driven generative models incorporated with physical information to iteratively refine initial airfoil shapes, resulting in improved aerodynamic performances and reduced constraint violations. …”
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On Designing Low-Risk Honeypots Using Generative Pre-Trained Transformer Models With Curated Inputs by Jarrod Ragsdale, Rajendra V. Boppana

“…Large-scale text-generating models, commonly referred to as Large Language Models (LLMs), have seen wide implementation using generative-pretrained transformer (GPT) models. …”
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Process-Based Modeling of the High Flow of a Semi-Mountain River under Current and Future Climatic Conditions: A Case Study of the Iya River (Eastern Siberia) by Andrey Kalugin

“…Possible changes in the characteristics of high flow over summers in the 21st century were calculated using the atmosphere–ocean general circulation model (AOGCM) and the Hadley Centre Global Environment Model version 2-Earth System (HadGEM2-ES) as the boundary conditions in the runoff generation model. Anomalies in values were estimated for the middle and end of the current century relative to the observed runoff over the period 1990–2019. …”
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Automatic mechanistic inference from large families of Boolean models generated by Monte Carlo tree search by Bryan J. Glazer, Jonathan T. Lifferth, Carlos F. Lopez, Carlos F. Lopez

“…We demonstrate that MC-Boomer works well at reconstructing randomly generated models. Then, using single time point measurements and reasonable biological constraints, our method generates hundreds of thousands of candidate models that match experimentally validated in-vivo behaviors of the Drosophila segment polarity network. …”
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Insights from molecular dynamics simulations: structural basis for the V567D mutation-induced instability of zebrafish alpha-dystroglycan and comparison with the murine model. by Davide Pirolli, Francesca Sciandra, Manuela Bozzi, Bruno Giardina, Andrea Brancaccio, Maria Cristina De Rosa

“…A comparative study has been also carried out on our previously generated model of murine alpha-DG C-terminal domain including the I591D mutation, which is topologically equivalent to the V567D mutation found in zebrafish. …”
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Deep convolutional and conditional neural networks for large-scale genomic data generation. by Burak Yelmen, Aurélien Decelle, Leila Lea Boulos, Antoine Szatkownik, Cyril Furtlehner, Guillaume Charpiat, Flora Jay

“…Applications of generative models for genomic data have gained significant momentum in the past few years, with scopes ranging from data characterization to generation of genomic segments and functional sequences. …”
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Monitoring Coastal Erosion Using Remote Images: Comparison between Physically and Remotely Acquired Data on a Limestone Coast by Joanna Causon Deguara, Ritienne Gauci, Rob Inkpen

“…The use of unmanned aerial vehicle (UAV) technology and related software has facilitated the monitoring of coastal areas, by generating models from which 2D and 3D measurements can be derived. …”
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New records and modelling the impacts of climate change on the black-tailed marmosets. by Almério Câmara Gusmão, Jôine Cariele Evangelista-Vale, João Carlos Pires-Oliveira, Adrian A Barnett, Odair Diogo da Silva

“…We recommend that further studies be carried out to confirm the presence of the species in adjacent areas, those indicated by generated models as being potential environmentally suitable. …”
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Beyond ℓ1 sparse coding in V1. by Ilias Rentzeperis, Luca Calatroni, Laurent U Perrinet, Dario Prandi

“…Traditionally, to replicate such biological sparsity, generative models have been using the ℓ1 norm as a penalty due to its convexity, which makes it amenable to fast and simple algorithmic solvers. …”
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Theoretıcal Optımızatıon Of The P-N Type Semıconductor Materıal Paır In Thermoelectrıc Generator That Achıevement Exhaust Waste Heat Recovery by Ümit TOPALCI, Habib GÜRBÜZ, Hüsameddin AKÇAY, Selim DEMİRTÜRK

“…The thermoelectric generator using thermoelectric modules created from the determined p-n pairs was analyzed using the theoretical thermoelectric generator model developed in the Matlab/Simulink program in the previous study. …”
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Multi-Prior Twin Least-Square Network for Anomaly Detection of Hyperspectral Imagery by Jiaping Zhong, Yunsong Li, Weiying Xie, Jie Lei, Xiuping Jia

“…Despite the extensive success of hyperspectral interpretation techniques based on generative adversarial networks (GANs), applying trained GAN models to hyperspectral anomaly detection remains promising but challenging. Previous generative models can accurately learn the complex background distribution of HSI and typically convert the high-dimensional data back to the latent space to extract features to detect anomalies. …”
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Survey on Generative Adversarial Behavior in Artificial Neural Tasks by Roheen Qamar, Naomi Bajao, Iswanto Suwarno, Fareed Ahmed Jokhio

“…Generative Adversarial Networks (GANs) are a unique class that has recently received a lot of interest due to the popularity of deep generative models. GANs implicitly distribute complex and high-resolution images, sounds, and data. …”
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Scaling of urban amenities: generative statistics and implications for urban planning by Talia Kaufmann, Laura Radaelli, Luis M. A. Bettencourt, Erez Shmueli

“…We use these size-specific statistical findings to produce generative models for the expected amenity abundances of any US city. …”
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Intelligent auxiliary system for music performance under edge computing and long short-term recurrent neural networks. by Yi Wang

“…In addition, image description generative models with attention mechanisms are adopted technically. …”
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Similarity-assisted variational autoencoder for nonlinear dimension reduction with application to single-cell RNA sequencing data by Gwangwoo Kim, Hyonho Chun

“…Abstract Background Deep generative models naturally become nonlinear dimension reduction tools to visualize large-scale datasets such as single-cell RNA sequencing datasets for revealing latent grouping patterns or identifying outliers. …”
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Knowledge Graph-to-Text Model Based on Dynamic Memory and Two-layer Reconstruction Reinforcement by MA Tinghuai, SUN Shengjie, RONG Huan, QIAN Minfeng

“…Knowledge Graph-to-Text is a new task in the field of knowledge graph,which aims to transform knowledge graph into readable text describing these knowledge.With the deepening of research in recent years,the generation technology of Graph-to-Text has been applied to the fields of product review generation,recommendation explanation generation,paper abstract generation and so on.The translation model in the existing methods adopts the method of first-plan-then-realization,which fails to dynamically adjust the planning according to the generated text and does not track the static content planning,resulting in incohe-rent semantics before and after the text.In order to improve the semantic coherence of generated text,a Graph-to-Text model based on dynamic memory and two-layer reconstruction enhancement is proposed in this paper.Through three stages of static content planning,dynamic content planning and two-layer reconstruction mechanism,this model makes up for the structural difference between knowledge graph and text,focusing on the content of each triple while generating text.Compared with exis-ting generation models,this model not only compensates for the structural differences between knowledge graphs and texts,but also improves the ability to locate key entities,resulting in stronger factual consistency and semantics in the generated texts.In this paper,experiments are conducted on the WebNLG dataset.The results show that,compared with the current exis-ting models in the task of Graph-to-Text,the proposed model generates more accurate content planning.The logic between the sentences of the generated text is more reasonable and the correlation is stronger.The proposed model outperforms existing methods on me-trics such as BLEU,METEOR,ROUGE,CHRF++,etc.…”
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Antibody designing against IIIabc junction (JIIIabc) of HCV IRES through affinity maturation; RNA-Antibody docking and interaction analysis. by Saima Ejaz, Rehan Zafar Paracha, Sadaf Ejaz, Zunera Jamal

“…Complementarity determining regions of reported Fab (wild type) were assessed and docked with IRES. Best generated model of Fab was selected and subjected to alanine scanning Three sets of insilico mutations for variants (V) designing were selected; single (1-71), double (a-j) and triple (I-X). …”
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Variational Bayesian Variable Selection for High-Dimensional Hidden Markov Models by Yao Zhai, Wei Liu, Yunzhi Jin, Yanqing Zhang

“…As a rapid substitute, variational approximation has become a noteworthy and effective approximate inference approach, particularly in recent years, for representation learning in deep generative models. However, there has been limited exploration of variational inference for HMMs with high-dimensional covariates. …”
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Diffusion Subspace Clustering for Hyperspectral Images by Jiaxin Chen, Shujun Liu, Zhongbiao Zhang, Huajun Wang

“…Specifically, due to the diffusion probabilistic model (DPM) learning raw object data distribution to generate data of the same distribution, which has received wide attention in generation tasks and outperforms other generative models significantly, we attempt to apply the DPM in the field of feature extraction. …”
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