Addressing the class imbalance in tabular datasets from a generative adversarial network approach in supervised machine learning by Máximo E Sánchez-Gutiérrez, Pedro P González-Pérez

“…Besides, generative adversarial networks, a deep learning technique for building generative models, offer an alternative machine learning technique that is particularly well suited to address the class imbalance problem. …”
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RailFOD23: A dataset for foreign object detection on railroad transmission lines by Zhichao Chen, Jie Yang, Zhicheng Feng, Hao Zhu

“…Taking a unique approach and leveraging large-scale models such as ChatGPT (Chat Generative Pre-trained Transformer) and text-to-image generation models, we synthesize a series of foreign object data. …”
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Hierarchical Keyword Generation Method for Low-Resource Social Media Text by Xinyi Guan, Shun Long

“…Specifically, the text segment is introduced as a hierarchical unit of social media text to construct a hierarchical model structure and design a text segment recovery task for self-supervised training of the model, which not only improves the ability of the model to extract features from social media text, but also reduces the dependence of the keyword generation model on the labeled data in the social media domain. …”
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3D Carbonate Digital Rock Reconstruction by Self-Attention Network and GAN Structure by Bin Wang, Jiahao Wang, Ye Liu

“…This manuscript intricately explores the deployment of state-of-the-art generative models for the meticulous reconstruction of digital rock core samples. …”
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Identifying Requirements Association Based on Class Diagram Using Semantic Similarity by Hernawati Susanti Samosir, Daniel Siahaan

“…It provides necessary information for developers during decision-making processes, such as change management, development milestones, bug prediction, cost estimation, and work breakdown structure generation. Modeling association between requirements became a focus of software requirements researchers. …”
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Inelastic longitudinal electron scattering C42 form factors in42Ti nucleus by Firas Y. Khudayer

“…Modern model space effective interactions like FPD6 and GXPF1 have been used to generate model space vectors and harmonic oscillator wave function as a single particle wave function. …”
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Improving the quality of chemical language model outcomes with atom-in-SMILES tokenization by Umit V. Ucak, Islambek Ashyrmamatov, Juyong Lee

“…We believe that the atom-in-SMILES tokenization has a great potential to be adopted by broad related scientific communities, as it provides chemically accurate, tailor-made tokens for molecular property prediction, chemical translation, and molecular generative models.…”
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Waste Detection System Based on Data Augmentation and YOLO_EC by Jinhao Fan, Lizhi Cui, Shumin Fei

“…First of all, because of the current shortage of multi-objective waste classification datasets, the heavy workload of human data collection, and the limited improvement of data features by traditional data augmentation methods, DCGAN (deep convolution generative adversarial networks) was optimized by improving the loss function, and an image-generation model was established to realize the generation of multi-objective waste images; secondly, with YOLOv4 (You Only Look Once version 4) as the basic model, EfficientNet is used as the backbone feature extraction network to realize the light weight of the algorithm, and at the same time, the CA (coordinate attention) attention mechanism is introduced to reconstruct the MBConv module to filter out high-quality information and enhance the feature extraction ability of the model. …”
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A Higher Order Mining Approach for the Analysis of Real-World Datasets by Shahrooz Abghari, Veselka Boeva, Jens Brage, Håkan Grahn

“…In cases in which significant differences are observed, further analysis is performed by integrating the generated models into a consensus clustering and applying an MST to identify deviating behaviours. …”
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How to model wireless mesh networks topology by Sanni, Mistura L., Hassan Abdalla Hashim, Aisha, Anwar, Farhat, Ahmed, G S M, Ali, Sellami

“…However, the existing topology generators model geographic topologies which constitute different architectures, thus may not be suitable in Wireless Mesh Networks scenarios. …”
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Higgs boson studies at the Tevatron by Aaltonen, T, Abazov, V, Abbott, B, Acharya, B, Adams, M, Adams, T, Agnew, J, Alexeev, G, Alkhazov, G, Alton, A, Amerio, S, Amidei, D, Anastassov, A, Annovi, A, Antos, J, Apollinari, G, Appel, J, Arisawa, T, Artikov, A, Asaadi, J, Ashmanskas, W, Askew, A, Atkins, S, Auerbach, B, Augsten, K

“…The searches are also interpreted in the context of fermiophobic and fourth generation models. We observe a significant excess of events in the mass range between 115 and 140 GeV/c2. …”

osl-dynamics: a toolbox for modelling fast dynamic brain activity by Gohil, C, Huang, R, Roberts, E, van Es, MWJ, Quinn, AJ, Vidaurre, D, Woolrich, MW

“…At its core are machine learning generative models that are able to adapt to the data and learn the timing, as well as the spatial and spectral characteristics, of brain activity with few assumptions. osl-dynamics incorporates state-of-the-art approaches that can be, and have been, used to elucidate brain dynamics in a wide range of data types, including magneto/electroencephalography, functional magnetic resonance imaging, invasive local field potential recordings and electrocorticography. …”

Non-adversarial training of neural SDEs with signature kernel scores by Issa, Z, Horvath, B, Lemercier, M, Salvi, C

“…Neural SDEs are continuous-time generative models for sequential data. State-of-the-art performance for irregular time series generation has been previously obtained by training these models adversarially as GANs. …”

A Three-Generation Calabi-Yau Manifold with Small Hodge Numbers by Braun, V, Candelas, P, Davies, R

“…This strongly suggests that there is a heterotic vacuum for this manifold that derives from the 3 generation model on the quotient of Y. The manifold Y may also be realised as a hypersurface in the toric variety. …”

osl-dynamics, a toolbox for modeling fast dynamic brain activity by Gohil, C, Huang, R, Roberts, E, van Es, MWJ, Quinn, AJ, Vidaurre, D, Woolrich, MW

“…At its core are machine learning generative models that are able to adapt to the data and learn the timing, as well as the spatial and spectral characteristics, of brain activity with few assumptions. osl-dynamics incorporates state-of-the-art approaches that can be, and have been, used to elucidate brain dynamics in a wide range of data types, including magneto/electroencephalography, functional magnetic resonance imaging, invasive local field potential recordings, and electrocorticography. …”

Mouse models for inherited endocrine and metabolic disorders. by Piret, SE, Thakker, R

“…Moreover, methods have been developed to alter the expression of genes in the mouse, thereby generating models for human diseases, which may be due to loss- or gain-of-function mutations. …”

Relational persistent homology for multispecies data with application to the tumor microenvironment by Stolz, BJ, Dhesi, J, Bull, JA, Harrington, HA, Byrne, HM, Yoon, IHR

“…We demonstrate that relational topological features can extract biological insight, including the dominant immune cell phenotype (an important predictor of patient prognosis) and the parameter regimes of a data-generating model. The methods provide a quantitative perspective on the relational analysis of multispecies spatial data, overcome the limits of traditional PH, and are readily computable.…”

Climate projections of future extreme events in Malaysia by Abdul Halim, Syafrina, M. D., Zalina, A., Norzaida

“…The proposed method, the Advanced Weather Generator model is constructed based on thirty years of hourly rainfall data from forty stations. …”
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Configuring suitable landfill with GIS-network analyst case study municipal of Batam - Indonesia by Evy Yusriani, Evy Yusriani

“…This study meant to apply Network Analysis in GIS to develop scenario generation model and assess alternative landfill sites in Batam City based on the economical aspects. …”
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Stochastic generation of hourly rainstorm events in Johor by Nojumuddin, Nur Syereena, Yusof, Fadhilah, Yusop, Zulkifli

“…Therefore, this paper presents a Monte-Carlo based stochastic hourly rainfall generation model to complement the unavailable data. The Monte Carlo simulation used in this study is based on the best fit of storm characteristics. …”