Results 131 to 140 of about 537,310 (265)
Editorial: Graph representation learning in biological network. [PDF]
Front Bioinform, 2023 Roy S, Guzzi PH, Kalita J.
europepmc +1 more source
Scalable Task Planning via Large Language Models and Structured World Representations
Advanced Robotics Research, EarlyView.This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari +4 more
wiley +1 more source
Disentangled Generative Graph Representation Learning
Recently, generative graph models have shown promising results in learning graph representations through self-supervised methods. However, most existing generative graph representation learning (GRL) approaches rely on random masking across the entire graph, which overlooks the entanglement of learned representations.
Hu, Xinyue +5 more
openaire +2 more sources
Stable Imitation of Multigait and Bipedal Motions for Quadrupedal Robots Over Uneven Terrains
Advanced Robotics Research, EarlyView.How are quadrupedal robots empowered to execute complex navigation tasks, including multigait and bipedal motions? Challenges in stability and real‐world adaptation persist, especially with uneven terrains and disturbances. This article presents an imitation learning framework that enhances adaptability and robustness by incorporating long short‐term ...
Erdong Xiao +3 more
wiley +1 more source
Advanced Robotics Research, EarlyView.An AI‐powered, robot‐assisted framework automatically produces, images, and analyzes 3D tumor spheroids to evaluate drug efficacy. Integrated modules handle spheroid formation, live/dead staining, brightfield imaging, and automated image analysis, including spheroid segmentation, viability and metrics to assess the drug treatment efficacy. The workflow
Dalia Mahdy +13 more
wiley +1 more source
Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
Advanced Robotics Research, EarlyView.BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source
Subgraph extraction and graph representation learning for single cell Hi-C imputation and clustering. [PDF]
Brief Bioinform, 2023 Zheng J, Yang Y, Dai Z.
europepmc +1 more source
Asymmetry in Skipping Enhances Viability Against Control Input Noise
Advanced Robotics Research, EarlyView.Quadruped animals use asymmetric galloping gaits at high speeds, yet the functional role of this asymmetry remains unclear. This study shows that left–right asymmetry in touchdown angles enhances robustness to control noise. Using a simple two‐legged locomotion model and viability theory, it demonstrates that asymmetric skipping substantially enlarges ...
Yuichi Ambe, Alvin So, Shinya Aoi
wiley +1 more source
Advancing Biomedicine with Graph Representation Learning: Recent Progress, Challenges, and Future Directions. [PDF]
Yearb Med Inform, 2023 Li F, Nian Y, Sun Z, Tao C.
europepmc +1 more source