Results 181 to 190 of about 8,738,264 (288)

UNCERTAINTY AWARE TEMPORAL RELATIONSHIP MODELLING IN KNOWLEDGE GRAPHS

PTRM models temporal uncertainty in knowledge graphs through distributional event embeddings and probabilistic overlap computation, replacing fixed temporal thresholds with learned probability distributions.
Ramachandran, Deepa
core   +1 more source

Temporal knowledge graph reasoning using global and recent history information. [PDF]

Sci Rep
Wang C, Cao J, Guo W, Hu J, Hu Y, Liu Y, Li Y, Tian H, Lu P, Zhao W, Yin Z.   +10 more
europepmc   +1 more source

Machine learning driven many‐objective moving horizon scheduling optimization

AIChE Journal, EarlyView.
Abstract Industrial electrification can decarbonize chemical manufacturing, but it exposes operations to volatile electricity prices and carbon intensities. This work develops a machine learning‐enhanced many‐objective moving horizon scheduling framework that predicts objective correlation groupings from 48‐hour price and emission‐intensity profiles ...
Hongxuan Wang, Andrew Allman
wiley   +1 more source

Adaptive feature fusion network for machine fault diagnosis with multiple knowledge based graphs. [PDF]

Sci Rep
Liu C, Han J, Zhang Y, Zhang Z, Gao H, Jia L.   +5 more
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Analysis of the interaction network relationship between drugs using a graph neural network. [PDF]

Front Pharmacol
Chai Z, Wang J, Du H.
europepmc   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

From graph models to intelligent decision-making: a review of spatio-temporal graph neural networks for regional disease risk prediction and etiology mining. [PDF]

Front Public Health
Chen Y, Qin X, Chen S.
europepmc   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

Advanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser, Haseeb Muhammad, Junaid Younas, Gillian Lovell, Bianca Migliori, Andreas Dengel, Sheraz Ahmed   +6 more
wiley   +1 more source

Graph neural networks based log anomaly detection and explanation. [PDF]

Data Min Knowl Discov
Li Z, Shi J, van Leeuwen M.
europepmc   +1 more source