Optimal transport based simulation methods for deep probabilistic models by Thornton, J

“…The remaining two works contribute to the field of diffusion based generative modelling through the Schrödinger Bridge. First, we connect diffusion models to the Schrödinger Bridge, coined the Diffusion Schrödinger Bridge. …”

Benefits of multi-modal fusion analysis on a large-scale dataset: life-span patterns of inter-subject variability in cortical morphometry and white matter microstructure. by Groves, A, Smith, S, Fjell, A, Tamnes, C, Walhovd, K, Douaud, G, Woolrich, M, Westlye, LT

“…This exploratory approach automatically generates models to explain structure in the data, and may prove especially powerful for large-scale studies, where the population variability can be explored in increased detail.…”

Experience-based object detection for robot perception by Hawke, J

“…The network learns a representation of the operating environment, generating model parameters based on the input image. This offers a general approach to constructing place specific object detectors independently of localisation, with the potential to operate on larger scales with many different environments.…”

Exchange market pressure in identifying currency crisis and its effectiveness in monetary policy in selected Asian countries by Tey, Sheik Kyin

“…Thus, in this study, the main findings are: (1) more flexible currency is associated with higher volatility; (2) the higher degree of trade openness assists to amplify the impact of shocks in the economy; (3) the currency crisis is transmittable among major trade partners and/or competitors; (4) the economic fundamental is related to the incidence of currency crisis and supports the first-generation model of speculative attacks; (5) the responses of the currency pressure to monetary policies shocks are varied between Asian financial crisis and global financial crisis; and (6) the monetary policy stances are ineffective in decreasing currency pressure. …”
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Modeling 3D buildings of LOD2 from airborne point cloud using unsupervised classification by Janarthanan, Sethu Madhavan

“…This study aims to generate 3D city model from the airborne LiDAR and incorporate them in CityServer3D where the 3D geodatabase is created. All the generated models are based on the standard CityGML format. …”
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Remote protein homology detection and fold recognition using two-layer support vector machine classifiers by Muda, Hilmi M., Saad, Puteh, Othman, Razib M.

“…To detect protein structural classes from protein primary sequence information, homology-based methods have been developed, which can be divided to three types: discriminative classifiers, generative models for protein families and pairwise sequence comparisons. …”

Utilization of biogas released from palm oil mill effluent for power generation using self-preheated reactor by Hosseini, Seyed Ehsan, A. Wahid, Mazlan

“…A new design of lab-scale flameless reactor called self-preheated flameless combustion (SPFC) system is presented and employed in power generation modeling. In SPFC system, the flameless chamber is employed as a heater to preheat an oxidizer over the self-ignition temperature of the fuel. …”

Construction of seasonal based depth duration frequency curves by Nojumuddin, Nur Syereena

“…In Malaysia, the frequent occurrence of flood especially urban areas has caused tremendous losses and damages to properties and environment. Rainfall generation model is crucial since the adequate long historical data sets are frequently not available. …”
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Hub angle control of flexible manipulator based on bacterial foraging optimization by Mohd. Salme, Muhammad Nazri, Hadi, Muhamad Sukri, Jamali, Annisa, Mohd. Yatim, Hanim, Ab. Talib, Mat Hussin, Mat Darus, Intan Zaurah

“…Bacterial Foraging Optimization (BFO) is used to develop the modelling by SI technique to obtain the mathematical models. The generated model’s performance is assessed using three methods: minimum mean square error (MSE), correlation tests, and stability test in pole-zero diagram. …”

Learning visual representations without human supervision by Xie, Jiahao

“…In particular, we leverage the explicit data generation ability of generative models to address the data-hungry and label-expensive issues for certain downstream tasks like instance segmentation, especially for rare and novel categories. …”
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Bacterial Succession in Microbial Biofilm as a Potential Indicator for Postmortem Submersion Interval Estimation by Finkelbergs Dmitrijs, Juanjuan Guo, Juanjuan Guo, Juanjuan Guo, Yecao Huang, Yafei Liu, Xinyue Fang, Kankan Jiang, Lagabaiyila Zha, Jifeng Cai, Xiaoliang Fu, Xiaoliang Fu

“…The machine learning algorithm-generated models based on such temporal succession patterns have been developed for the postmortem interval (PMI) estimation. …”
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Deep Learning Models for Predicting Gas Adsorption Capacity of Nanomaterials by Wenjing Guo, Jie Liu, Fan Dong, Ru Chen, Jayanti Das, Weigong Ge, Xiaoming Xu, Huixiao Hong

“…Our results demonstrated that deep learning algorithms have a great potential to generate models that can accurately predict the gas adsorption capacities of MOFs.…”
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SPEAR: The Next Generation GFDL Modeling System for Seasonal to Multidecadal Prediction and Projection by Thomas L. Delworth, William F. Cooke, Alistair Adcroft, Mitchell Bushuk, Jan‐Huey Chen, Krista A. Dunne, Paul Ginoux, Richard Gudgel, Robert W. Hallberg, Lucas Harris, Matthew J. Harrison, Nathaniel Johnson, Sarah B. Kapnick, Shian‐Jian Lin, Feiyu Lu, Sergey Malyshev, Paul C. Milly, Hiroyuki Murakami, Vaishali Naik, Salvatore Pascale, David Paynter, Anthony Rosati, M.D. Schwarzkopf, Elena Shevliakova, Seth Underwood, Andrew T. Wittenberg, Baoqiang Xiang, Xiaosong Yang, Fanrong Zeng, Honghai Zhang, Liping Zhang, Ming Zhao

“…Abstract We document the development and simulation characteristics of the next generation modeling system for seasonal to decadal prediction and projection at the Geophysical Fluid Dynamics Laboratory (GFDL). …”
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Deep learning strategies for addressing issues with small datasets in 2D materials research: Microbial Corrosion by Cody Allen, Cody Allen, Cody Allen, Shiva Aryal, Tuyen Do, Rishav Gautum, Md Mahmudul Hasan, Md Mahmudul Hasan, Md Mahmudul Hasan, Bharat K. Jasthi, Bharat K. Jasthi, Bharat K. Jasthi, Etienne Gnimpieba, Etienne Gnimpieba, Venkataramana Gadhamshetty, Venkataramana Gadhamshetty, Venkataramana Gadhamshetty

“…Here, we investigated two different deep generative models, namely variation autoencoder (VAE) and generative adversarial network (GAN) for generating synthetic data for expanding small experimental datasets. …”
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Can in vitro embryo production be estimated from semen variables in Senepol breed by using artificial intelligence? by Suzane Peres Campanholi, Sebastião Garcia Neto, Gabriel Martins Pinheiro, Marcelo Fábio Gouveia Nogueira, José Celso Rocha, João Diego de Agostini Losano, Adriano Felipe Perez Siqueira, Marcílio Nichi, Mayra Elena Ortiz D'Avila Assumpção, Andréa Cristina Basso, Fabio Morato Monteiro, Lindsay Unno Gimenes

“…A previous study identified three sperm subpopulations in such samples and the information used in tandem with other sperm quality variables to perform an AI analysis. AI analysis generated models that estimated IVEP based on the season, donor, percentage of viable oocytes, and 18 other sperm predictor variables. …”
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MeWEHV: Mel and Wave Embeddings for Human Voice Tasks by Andres Carofilis, Laura Fernandez-Robles, Enrique Alegre, Eduardo Fidalgo

“…Our approach allows a significant increase in the performance of state-of-the-art embedding generation models on all the tested datasets, with a low additional computational cost.…”
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A data-driven approach to predict the compressive strength of alkali-activated materials and correlation of influencing parameters using SHapley Additive exPlanations (SHAP) analys... by Xinliang Zheng, Yi Xie, Xujiao Yang, Muhammad Nasir Amin, Sohaib Nazar, Suleman Ayub Khan, Fadi Althoey, Ahmed Farouk Deifalla

“…The assessment of the statistical parameters of generated models revealed that the MEP model was more effective. …”
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A Hybrid Method for 3D Reconstruction of MR Images by Loubna Lechelek, Sebastien Horna, Rita Zrour, Mathieu Naudin, Carole Guillevin

“…In procedures for intervention or radiation treatment planning, the generated models should be accurate and reflect the natural appearance. …”
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Modeling Energy LED Light Consumption Based on an Artificial Intelligent Method Applied to Closed Plant Production System by Ernesto Olvera-Gonzalez, Martín Montes Rivera, Nivia Escalante-Garcia, Eduardo Flores-Gallegos

“…We propose two nonlinear models, i.e., genetic programing (GP) and feedforward artificial neural networks (FNNs) to predict energy consumption in CPPS. The generated models use the following input variables: intensity, red light component, blue light component, green light component, and white light component; and the following operation modes: continuous and pulsed light including pulsed frequency, and duty cycle as well energy consumption as output. …”
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Attribute-Guided Generative Adversarial Network With Improved Episode Training Strategy for Few-Shot SAR Image Generation by Yuanshuang Sun, Yinghua Wang, Liping Hu, Yuanyuan Huang, Hongwei Liu, Siyuan Wang, Chen Zhang

“…Deep-learning-based models usually require a large amount of data for training, which guarantees the effectiveness of the trained model. Generative models are no exception, and sufficient training data are necessary for the diversity of generated images. …”
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