Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) Studies on α1A-Adrenergic Receptor Antagonists Based on Pharmacophore Mo... by Mu Yuan, Minsheng Chen, Biyun Huang, Xin Zhao, Hong Ji

“…The high correlation between the cross-validated/predicted and experimental activities of a test set of 12 ligands revealed that the CoMFA and CoMSIA models were robust (r2pred/CoMFA = 0.694; r2pred/CoMSIA = 0.671). The generated models suggested that electrostatic, hydrophobic, and hydrogen bonding interactions play important roles between ligands and receptors in the active site. …”
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Spatial clustering in vaccination hesitancy: The role of social influence and social selection. by Lucila G Alvarez-Zuzek, Casey M Zipfel, Shweta Bansal

“…Finally, we propose, and evaluate the effectiveness of two novel intervention strategies to diminish hesitant behavior. Our generative modeling approach informed by unique empirical data provides insights on the role of complex social processes in driving spatial heterogeneity in vaccine hesitancy.…”
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CEG: A joint model for causal commonsense events enhanced story ending generation. by Yushi Zhang, Yan Yang, Ming Gu, Feng Gao, Chengcai Chen, Liang He

“…Specifically, we first develop a commonsense events inference model trained on GLUCOSE, which converts static knowledge into a dynamic generation model to discover unseen knowledge. It uses prompts to produce various commonsense events behind the stories as pseudo-labels of the dataset. …”
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Artificial intelligence driven design of catalysts and materials for ring opening polymerization using a domain-specific language by Nathaniel H. Park, Matteo Manica, Jannis Born, James L. Hedrick, Tim Erdmann, Dmitry Yu. Zubarev, Nil Adell-Mill, Pedro L. Arrechea

“…These results reveal the versatility of CMDL and how it facilitates translation of historical data into meaningful predictive and generative models to produce experimentally actionable output.…”
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Comparing Classical and Quantum Generative Learning Models for High-Fidelity Image Synthesis by Siddhant Jain, Joseph Geraci, Harry E. Ruda

“…We undertake a comprehensive performance assessment of QBMs in comparison to established generative models in the field: Restricted Boltzmann Machines (RBMs), Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Denoising Diffusion Probabilistic Models (DDPMs). …”
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PHARMACOECONOMIC EVALUATION OF INFLUENZA AND PNEUMOCOCCAL VACCINATION IN EMPLOYEES OF THE JOINT STOCK COMPANY "RUSSIAN RAILWAYS" (JSCO "RZD") ON INVESTMENT FOR THE EMPLOYER by D. A. Zhukov

“…According to the generated modelling, the pneumococcal (PPSV23) immunization programme became cost-effective starting from the second year after vaccination and should continue to increase.…”
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Open Reading Frame 4 protein as potential drug target for HEV: Structural evaluation through computational approaches by Zoya Shafat, Shama Parveen

“…The 3-dimensional (3D) structures of the target protein were designed using homology modelling algorithms. The generated models were assessed through structure verification tool PROCHECK. …”
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Impersonation Attack Detection in Mobile Edge Computing by Levering SARSA Technique in Physical Layer Security by Xiaodan Yan, Ke Yan, Meezan Ur Rehman, Sami Ullah

“…We construct a system model of MEC, a key generation model (KGM), and an impersonation attack model (IAM). …”
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Deep learning model-based brand design 3D image construction by Huang Zeping, Chen Mengtian

“…The analysis of the results shows that the CD value of the used model is 0.477 and the EMD value is 0.579, which makes the constructed 3D images with more obvious detail levels and more accurate structural design, while the model of Pixel2Mesh focuses more on surface information, so the generated model is more realistic and closer to the real image.…”
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The commoditization of AI for molecule design by Fabio Urbina, Sean Ekins

“…It will also describe how many groups have implemented generative models covering different architectures, for de novo design of molecules. …”
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Discovery of novel inhibitors of ghrelin O-acyltransferase enzyme: an in-silico approach by Faezeh Sadat Hosseini, Alireza Ghassempour, Massoud Amanlou

“…Subsequently, the generated model was stabilized by molecular dynamics simulation. …”
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Pixel art character generation as an image-to-image translation problem using GANs by Flávio Coutinho, Luiz Chaimowicz

“…Then, we present an architecture of deep generative models that takes as input an image of a character in one domain (pose) and transfers it to another. …”
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UBMTR: Unsupervised Boltzmann machine-based time-aware recommendation system by GM Harshvardhan, Mahendra Kumar Gourisaria, Siddharth Swarup Rautaray, Manjusha Pandey

“…In the paradigm of generative modelling, restricted Boltzmann machines (RBMs) are used to solve complex tasks such as feature extraction, neuroimaging, collaborative filtering, radar target cognition, etc. …”
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Learning rule sets from survival data by Łukasz Wróbel, Adam Gudyś, Marek Sikora

“…Extensive experiments show LR-Rules to generate models of superior accuracy and comprehensibility. …”
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Automatic classification of medical X‐ray images using a bag of visual words by Mohammad Reza Zare, Ahmed Mueen, Woo Chaw Seng

“…The accuracy rate obtained by each generated model outperformed the results obtained by only one model on the entire dataset.…”
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AORM: Fast Incremental Arbitrary-Order Reachability Matrix Computation for Massive Graphs by Sung-Soo Kim, Young-Kuk Kim, Young-Min Kang

“…We conduct extensive experimental studies with twenty synthetic networks generated from five random graph generation models and twenty massive real-world networks. …”
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Smart Glass System Using Deep Learning for the Blind and Visually Impaired by Mukhriddin Mukhiddinov, Jinsoo Cho

“…The system is divided into four models: a low-light image enhancement model, an object recognition and audio feedback model, a salient object detection model, and a text-to-speech and tactile graphics generation model. Thus, this system was developed to assist in the following manner: (1) enhancing the contrast of images under low-light conditions employing a two-branch exposure-fusion network; (2) guiding users with audio feedback using a transformer encoder–decoder object detection model that can recognize 133 categories of sound, such as people, animals, cars, etc., and (3) accessing visual information using salient object extraction, text recognition, and refreshable tactile display. …”
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CEG: A joint model for causal commonsense events enhanced story ending generation by Yushi Zhang, Yan Yang, Ming Gu, Feng Gao, Chengcai Chen, Liang He

“…Specifically, we first develop a commonsense events inference model trained on GLUCOSE, which converts static knowledge into a dynamic generation model to discover unseen knowledge. It uses prompts to produce various commonsense events behind the stories as pseudo-labels of the dataset. …”
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Machine Learning Approach for Pump Price Prediction for the Philippines Post COVID-19 Pandemic and Amidst Russia-Ukraine Conflict by Sophia Bernadette R. Lunor, Jan Goran T. Tomacruz, Miguel Francisco M. Remolona, Joey D. Ocon

“…Mean Absolute Percent Error (MAPE) was used to evaluate accuracy. Generated models had MAPE values within the range 3.13 % - 12.67 %, which is within the range of MAPE values in oil and petroleum price prediction literature, 0.131 % - 19.2 %. …”
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Machine-learning models for spatially-explicit forecasting of future racial segregation in US cities by Tomasz F. Stepinski, Anna Dmowska

“…We investigated four different algorithms, Random Forest, Gradient Boosted Trees, Neural Network, and Self-Normalizing Net, and have found that Gradient Boosted Trees (GBT) yields the best predictions. Using the GBT-generated model we make a prediction of residential segregation in Cook County in the year 2030.…”
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