Zhiyuan Zeng*, Hamish Ivison*, Yiping Wang*, Lifan Yuan*, Shuyue Stella Li, Zhuorui Ye, Siting Li, Jacqueline He, Runlong Zhou, Tong Chen, Chenyang Zhao, Yulia ...

Only 32% of digital learning in the U.S. is currently personalized, according to a new study commissioned by Insights Learning and Development and conducted by the Association for Talent Development.

Abstract: Few-shot learning seeks to recognize novel classes from limited examples. Model-agnostic meta-learning (MAML), known for its simplicity and flexibility, learns an effective initialization ...

Learning control policies in simulation enables rapid, safe, and cost-effective development of advanced robotic capabilities. However, transferring these policies to the real world remains difficult ...

This study provides a useful application of computational modelling to examine how people with chronic pain learn under uncertainty, contributing to efforts to link pain with motivational processes.

Pathway’s post-transformer architecture BDH integrated with NVIDIA AI and AWS cloud infrastructure Pathway model’s continuous learning, efficiency, and live observability is powered by NVIDIA AI ...

Abstract: While control barrier functions (CBFs) are capable of providing safety guarantees, their effectiveness can degrade in the presence of model uncertainty and unexpected faults, particularly ...

Colleges and universities can leapfrog from personalized to N-of-1 precision learning by modernizing their data architecture, building dynamic learner profiles, and adopting computed curriculum. This ...

Adaptive learning systems (ALSs), powered by artificial intelligence (AI), represent a transformative approach to biotechnological and pharmaceutical education that addresses the critical limitations ...