A probabilistic approach for multiaxial fatigue criteria by M. Muñiz Calvente, S. Blasón, A. Fernández Canteli, A. de Jesús, J. Correia

“…Models proposed to study the multiaxial fatigue damage phenomenon generally lack probabilistic interpretation due to their deterministic form. …”
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The probabilistic and dynamic nature of perception in human generalization behavior by Kenny Yu, Wolf Vanpaemel, Francis Tuerlinckx, Jonas Zaman

“…The model analyzed continuous measures of perception and fear generalization to understand their relationship. …”
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Integration of Neural Embeddings and Probabilistic Models in Topic Modeling by Pantea Koochemeshkian, Nizar Bouguila

“…Our findings underscore the potential of leveraging hybrid architectures, marrying neural embeddings with advanced probabilistic modeling, to push the boundaries of topic modeling.…”
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A new probabilistic model with simulation studies: Model, theoretical insights, and its application to radar-based precipitation measurement by Xuejun Zhou, Abdulrahman Alomair, Abdulaziz S. Al Naim

“…As a result, our findings show that the CG-Rayleigh distribution is a significant addition to the class of probabilistic methods for modeling data related to the hydrological cycle.…”
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Probabilistic Assessment of Extreme Heat Stress on Indian Wheat Yields Under Climate Change by Mariam Zachariah, Arpita Mondal, Amir AghaKouchak

“…Abstract The wheat belt along the Indo‐Gangetic Plains (IGP) in India is an emergent hotspot of climate change‐driven crop loss threatening local food security. Using statistical Generalized Linear Models, observed temperature and wheat production data, we show an increase in magnitude, frequency and areal extent of heat stress episodes in the IGP region during 1967–2018. …”
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A probabilistic approach for multiaxial fatigue criteria by M. Muñiz Calvente, S. Blasón, A. Fernández Canteli, A. de Jesús, J. Correia

“…Models proposed to study the multiaxial fatigue damage phenomenon generally lack probabilistic interpretation due to their deterministic form. …”
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On the probabilistic description of the asynchronous phases occurrence in intermittent generalized synchronization regime of one-dimensional maps by Koronovskii, Aleksei Aleksandrovich, Moskalenko, Olga Igorevna, Selskii, Anton Olegovich

“…The purpose of the present study is to explain and describe (with the help of the probabilistic model) the process of breaking the stage of synchronous behavior and the emergence of a section of asynchronous dynamics in the regime of intermittent generalized chaotic synchronization in one-dimensional dynamical systems with discrete time. …”
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PROBABILISTIC MODEL FOR LONGITUDINAL ORIENTATION PROCESS OF CEREAL STRAW STALKS by Yury I. Yermolyev, Andrey V. Butovchenko, Sergey V. Belov, Roman E. Fomenko

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Reduced Order Probabilistic Emulation for Physics‐Based Thermosphere Models by Richard J. Licata, Piyush M. Mehta

“…In response, this work aims to employ a probabilistic machine learning (ML) method to create an efficient surrogate for the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIE‐GCM), a physics‐based thermosphere model. …”
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A survey of emerging applications of diffusion probabilistic models in MRI by Yuheng Fan, Hanxi Liao, Shiqi Huang, Yimin Luo, Huazhu Fu, Haikun Qi

“…Diffusion probabilistic models (DPMs) which employ explicit likelihood characterization and a gradual sampling process to synthesize data, have gained increasing research interest. …”
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Specific Mass Growth Rate of Sugar Crystals: Probabilistic Modeling by Denis V. Arapov, Vladimir A. Kuritsyn, Sergey M. Petrov, Nadezda M. Podgornova, Mariya A. Zaitseva

“…The article introduces a generalized mathematical model of specific growth rate of sugar crystals depending on temperature, solids, and the purity of solution, as well as on the concentration and average size of crystals. …”
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Exploring the Potential for Large Language Models to Demonstrate Rational Probabilistic Beliefs by Gabriel Freedman, Francesca Toni

“… Advances in the general capabilities of large language models (LLMs) have led to their use for information retrieval, and as components in automated decision systems. …”
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Transformer-Based Models for Probabilistic Time Series Forecasting with Explanatory Variables by Ricardo Caetano, José Manuel Oliveira, Patrícia Ramos

“…This study assesses how incorporating these variables enhances forecast accuracy, addressing a research gap in the comprehensive evaluation of explanatory variables within multiple Transformer-based models. Empirical results, based on the M5 dataset, show that incorporating explanatory variables generally improves forecasting performance. …”
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DR potential probabilistic forecasting model of load aggregators based on ensemble learning by YEERSEN Sailike, YANG Xi, LI Meiyi, LI Na, GE Xinxin, WANG Fei

“…Aiming at the shortcomings of generalization and reliability of a single-point forecasting model, this paper proposes an online DR potential probabilistic forecasting model of load aggregators based on ensemble learning, which can effectively improve the accuracy and generalization ability of the probabilistic forecasting model. …”
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Representation Learning for Vision-Based Autonomous Driving via Probabilistic World Modeling by Haoqiang Chen, Yadong Liu, Dewen Hu

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A Pythagorean Fuzzy Multigranulation Probabilistic Model for Mine Ventilator Fault Diagnosis by Chao Zhang, Deyu Li, Yimin Mu, Dong Song

“…In the process of building the mine ventilator fault diagnosis model, considering that probabilistic rough sets (PRSs) could reduce the errors triggered by incompleteness, inconsistency, and inaccuracy without needing any additional assumptions and Pythagorean fuzzy multigranulation rough sets (PF MGRSs) over the two universes’ model could effectively handle data representation, fusion, and analysis issues, we generalize the existing PF MGRSs over the two universes’ model to the PRS setting, as well as to further establish a novel model named Pythagorean fuzzy multigranulation probabilistic rough sets (PF MG-PRSs) over two universes. …”
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Hierarchical multimodel ensemble probabilistic forecasts for precipitation over East Asia by Luying Ji, Xiefei Zhi, Qixiang Luo, Yan Ji

“…In general, the improvement in precipitation probabilistic forecast skill of the h‐BMA model relative to the s‐BMA model surpasses that of the h‐EMOS model compared with the s‐EMOS model.…”
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Braneworld-f(R,T,G) by A.R.P. Moreira, Shi-Hai Dong

“…To achieve this, we consider a generalization of standard General Relativity. The stability of the model is evaluated through probabilistic measurements, revealing minimum points that represent the most probable and stable configurations of the brane for different values of the gravitational terms. …”
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Denoising diffusion probabilistic models for addressing data limitations in chest X-ray classification by Evi M.C. Huijben, Josien P.W. Pluim, Maureen A.J.M. van Eijnatten

“…To address these challenges, there has been a growing interest in the use of deep generative models to create synthetic training data, with denoising diffusion probabilistic models (DDPMs) recently gaining attention for their ability to produce realistic and high-quality images. …”
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Notes on Modified Planar Kelvin–Stuart Models: Simulations, Applications, Probabilistic Control on the Perturbations by Nikolay Kyurkchiev, Tsvetelin Zaevski, Anton Iliev, Vesselin Kyurkchiev, Asen Rahnev

“…In this paper, we propose a new modified planar Kelvin–Stuart model. We demonstrate some modules for investigating the dynamics of the proposed model. …”
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