ReMODE: a deep learning-based web server for target-specific drug design by Mingyang Wang, Jike Wang, Gaoqi Weng, Yu Kang, Peichen Pan, Dan Li, Yafeng Deng, Honglin Li, Chang-Yu Hsieh, Tingjun Hou

“…Recent advances in DL-based generative models have led to superior developments in de novo drug design. …”
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Visualisation of User Stories in UML Models: A Systematic Literature Review by Mohammad Nazrul Mornie, Nurfauza Jali, Syahrul Nizam Junaini, Edwin Mit, Cheah Wai Shiang, Suhaila Saee

“…The primary studies are reviewed to discover several important pieces of information, namely the challenges of designing UML models, NLP tools and techniques used to generate UML models, UML models generated, and validation methods used for measuring the accuracy of generated models. Finally, this study discusses important elements related to UML model generation using NLP tools and techniques.…”
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TraModeAVTest: Modeling Scenario and Violation Testing for Autonomous Driving Systems Based on Traffic Regulations by Chunyan Xia, Song Huang, Changyou Zheng, Zhen Yang, Tongtong Bai, Lele Sun

“…Subsequently, based on the coverage criteria of the Petri net model, it utilizes a search strategy to generate model paths that represent traffic regulations, and employs a parameter combination method to generate test cases that cover the model paths, to test the violation behaviors of autonomous driving systems. …”
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Horizontal Visibility in Forests by Mait Lang, Andres Kuusk, Kersti Vennik, Aive Liibusk, Kristina Türk, Allan Sims

“…Our analysis was based (1) on tree position maps and TLS data collected in 2013 and 2019 with three different scanners, and (2) on simulated digital twins of the forest stands, constructed with two pattern-generation models incorporating commonly used indices of tree position clumping. …”
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Estimating Algorithmic Information Using Quantum Computing for Genomics Applications by Aritra Sarkar, Zaid Al-Ars, Koen Bertels

“…Inferring algorithmic structure in data is essential for discovering causal generative models. In this research, we present a quantum computing framework using the circuit model, for estimating algorithmic information metrics. …”
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River Flow Estimation Using Artificial Intelligence and Fuzzy Techniques by Fatih Üneş, Mustafa Demirci, Martina Zelenakova, Mustafa Çalışıcı, Bestami Taşar, František Vranay, Yunus Ziya Kaya

“…The results obtained from the generated models were compared with the recorded values. …”
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BoYaTCN: Research on Music Generation of Traditional Chinese Pentatonic Scale Based on Bidirectional Octave Your Attention Temporal Convolutional Network by Fanzhi Jiang, Liumei Zhang, Kexin Wang, Xi Deng, Wanyan Yang

“…It combines clustering algorithms and deep learning-related algorithms to construct a three-dimensional sequential convolutional generation model 3D-SCN, a three-dimensional temporal convolutional attention model BoYaTCN. …”
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Industrial Soft Sensor Optimized by Improved PSO: A Deep Representation-Learning Approach by Alcemy Gabriel Vitor Severino, Jean Mário Moreira de Lima, Fábio Meneghetti Ugulino de Araújo

“…By doing this, the RB-PSOSAE computes hyperparameters capable of supporting the training process to generate models with improved generalization and relevant hidden features. …”
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A Variational Autoencoder Cascade Generative Adversarial Network for Scalable 3D Object Generation and Reconstruction by Min-Su Yu, Tae-Won Jung, Dai-Yeol Yun, Chi-Gon Hwang, Sea-Young Park, Soon-Chul Kwon, Kye-Dong Jung

“…Through comparative experiments with existing methods, we demonstrate the effectiveness of our approach in evaluating voxel quality, variations, and diversity. The generated models exhibit improved accuracy in 3D evaluation metrics and visual quality, making them valuable across various fields, including virtual reality, the metaverse, and gaming.…”
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Estimation of Pollutant Emissions in Real Driving Conditions Based on Data from OBD and Machine Learning by Néstor Diego Rivera-Campoverde, José Luis Muñoz-Sanz, Blanca del Valle Arenas-Ramirez

“…The main contribution of this article is that the generated model is stronger in different traffic conditions and presents good results at the speed interval with small differences at low average driving speeds because more than half of the vehicle’s trip occurs in urban areas, in completely random driving conditions. …”
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Sensitivity towards HDAC inhibition is associated with RTK/MAPK pathway activation in gastric cancer by Therese Seidlitz, Tim Schmäche, Fernando Garcίa, Joon Ho Lee, Nan Qin, Susan Kochall, Juliane Fohgrub, David Pauck, Alexander Rothe, Bon‐Kyoung Koo, Jürgen Weitz, Marc Remke, Javier Muñoz, Daniel E Stange

“…A combination of altered pathways can be associated with molecular subtypes of gastric cancer. In order to generate model systems to study the impact of different pathway alterations in a defined genetic background, we generated three murine organoid models: a RAS‐activated (KrasG12D, Tp53R172H), a WNT‐activated (Apcfl/fl, Tp53R172H), and a diffuse (Cdh1fl/fl, Apcfl/fl) model. …”
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The Benefit of Continuous Hydrological Modelling for Drought Hazard Assessment in Small and Coastal Ungauged Basins: A Case Study in Southern Italy by Davide Luciano De Luca, Ciro Apollonio, Andrea Petroselli

“…With this goal in mind, in this work we applied a synthetic rainfall generation model (STORAGE; stochastic rainfall generator), constituting the implementation of a modified version of Neymann-Scott rectangular pulse (NSRP) model, and a continuous rainfall-runoff framework (COSMO4SUB; continuous simulation modelling for small and ungauged basins) specifically designed for ungauged basins within a climate change context. …”
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Gen: A General-Purpose Probabilistic Programming System with Programmable Inference by Cusumano-Towner, Marco F., Saad, Feras A., Lew, Alexander, Mansinghka, Vikash K.

“…Gen programs can combine generative models written in Julia, neural networks written in TensorFlow, and custom inference algorithms based on an extensible library of Monte Carlo and numerical optimization techniques. …”
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Who Can Win a Single-Elimination Tournament? by Kim, Michael P., Suksompong, Warut, Williams, Virginia Vassilevska

“…We also establish new results for significantly more general generative models. Keywords: sports scheduling; single-elimination tournament; knockout tournament; manipulation…”
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Coresets for scalable Bayesian logistic regression by Huggins, Jonathan H., Campbell, Trevor David, Broderick, Tamara A

“…We provide theoretical guarantees on the size and approximation quality of the coreset - both for fixed, known datasets, and in expectation for a wide class of data generative models. Crucially, the proposed approach also permits efficient construction of the coreset in both streaming and parallel settings, with minimal additional effort. …”
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Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo by Terence, Yong Koon Beh, Swee, Chuan Tan, Hwee, Theng Yeo

“…When the data is imbalanced, these algorithms generate models that achieve good classification accuracy for the majority class, but poor accuracy for the minority class. …”
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Optimization of cultivation conditions in banana wastes for production of extracellular beta-glucosidase by Trichoderma harzianum Rifai efficient for in vitro inhibition of Macroph... by Khalili, Elham, Huyop, Fahrul, Manan, Fatin Myra Abd, Wahab, Roswanira Abdul

“…It is noteworthy that the low deviation values (0.09-0.44%) in the verification experiments (R1, R2 and R3) inferred the generated model was accurate to predict optimal cultivation conditions of T. harzianum Rifai. …”
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Data augmentation guided breast cancer diagnosis and prognosis using an integrated deep-generative framework based on breast tumor’s morphological information by Muhammad Sakib Khan Inan, Sohrab Hossain, Mohammed Nazim Uddin

“…To that end, this study investigates the potentiality of deep generative models including, the tabular variational autoencoder (TVAE) and the conditional generative adversarial network (CTGAN), to generate high-quality synthetic tabular data of breast tumors and support the diagnosis and prognosis of breast cancer. …”
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Entropy Generation Analysis of the Flow Boiling in Microgravity Field by Zijian Sun, Haochun Zhang, Qi Wang, Wenbo Sun

“…Entropy generation analysis of the flow boiling in microgravity field is conducted in this paper. A new entropy generation model based on the flow pattern and the phase change process is developed in this study. …”
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A One-Class Classifier for the Detection of GAN Manipulated Multi-Spectral Satellite Images by Lydia Abady, Giovanna Maria Dimitri, Mauro Barni

“…The current image generative models have achieved a remarkably realistic image quality, offering numerous academic and industrial applications. …”
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