PyReason: Software for open world temporal logic

D Aditya, K Mukherji, S Balasubramanian… - ar** for improving interpretability of convolutional neural networks
P Padalkar, H Wang, G Gupta - International Symposium on Practical …, 2024 - Springer
Within the realm of deep learning, the interpretability of Convolutional Neural Networks
(CNNs), particularly in the context of image classification tasks, remains a formidable …

Shaped-Charge Learning Architecture for the Human–Machine Teams

B Galitsky, D Ilvovsky, S Goldberg - Entropy, 2023 - mdpi.com
In spite of great progress in recent years, deep learning (DNN) and transformers have strong
limitations for supporting human–machine teams due to a lack of explainability, information …

A differentiable first-order rule learner for inductive logic programming

K Gao, K Inoue, Y Cao, H Wang - Artificial Intelligence, 2024 - Elsevier
Learning first-order logic programs from relational facts yields intuitive insights into the data.
Inductive logic programming (ILP) models are effective in learning first-order logic programs …