Tech Xplore

New memristor training method slashes AI energy use by six orders of magnitude

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...
Scientific American

The next AI revolution could start with world models

Why today’s AI systems struggle with consistency, and how emerging world models aim to give machines a steady grasp of space ...
IEEE

Quantum Machine Learning: Recent Advances, Challenges, and Perspectives

Abstract: This study presents a comprehensive survey on Quantum Machine Learning (QML) along with its current status, challenges, and perspectives. QML combines quantum computing and machine learning ...
Frontiers

KG2ML: Integrating Knowledge Graphs and Positive Unlabeled Learning for Identifying Disease-Associated Genes

The final, formatted version of the article will be published soon. Background Biomedical knowledge graphs (KGs), such as the Data Distillery Knowledge Graph (DDKG), capture known relationships among ...
GitHub

LASER: A Neuro-Symbolic Framework for Learning Spatial-Temporal Scene Graphs with Weak Supervision

This follow-up work demonstrates applying LASER for scene-graph generation in embodied agent environments. Answer: Ensure your CUDA Tool kit and your pytorch has the same version. Take 12.4 as an ...
IEEE

Deep Reinforcement Learning with Graph Neural Networks: An Indepth Analysis of Algorithms and Applications

Abstract: Deep Reinforcement Learning (DRL) enable several areas of artificial intelligence, including perception recognition, expert system, recommender program and game. Also, graph neural networks ...