Results 131 to 140 of about 224,550 (312)
Probabilistic Logic Programming
We present a new approach to probabilistic logic programs with a possible worlds semantics. Classical program clauses are extended by a subinterval of [0,1] that describes the range for the conditional probability of the head of a clause given its body.
openaire +1 more source
Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian +37 more
wiley +1 more source
This study introduces a framework that combines graph neural networks with causal inference to forecast recurrence and uncover the clinical and pathological factors driving it. It further provides interpretability, validates risk factors via counterfactual and interventional analyses, and offers evidence‐based insights for treatment planning ...
Jubair Ahmed +3 more
wiley +1 more source
Probabilistic Linear Logic Programming with an application to Bayesian Networks computations [PDF]
Matteo Acclavio, Roberto Maieli
openalex +2 more sources
Semirings for Probabilistic and Neuro-Symbolic Logic Programming [PDF]
Vincent Derkinderen +3 more
semanticscholar +1 more source
Real‐Time and Rapid Dynamic Missile Identification Utilizing a TiOx Memristor Array
Real‐time missile target identification is demonstrated using an artificial intelligence model based on step‐weighted long–short‐term memory networks and a TiOx memristor array. The approach classifies five projectile types with enhanced early‐stage prediction through data augmentation and custom training strategies. Achieving 94.4% accuracy, the model
Mingyu Kim, Gwanyeong Park, Gunuk Wang
wiley +1 more source
Programming with Personalized PageRank: A Locally Groundable First-Order Probabilistic Logic [PDF]
William Yang Wang +2 more
openalex +1 more source
FTGRN introduces an LLM‐enhanced framework for gene regulatory network inference through a two‐stage workflow. It combines a Transformer‐based model, pretrained on GPT‐4 derived gene embeddings and regulatory knowledge, with a fine‐tuning stage utilizing single‐cell RNA‐seq data.
Guangzheng Weng +7 more
wiley +1 more source
Review of Memristors for In‐Memory Computing and Spiking Neural Networks
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari +2 more
wiley +1 more source

