Abstract: Model-based reinforcement learning (RL) aims to learn the underlying dynamics of a given environment. The success of most existing works is built on the critical assumption that the dynamic ...
Abstract: In recent years, many discrete neural dynamics models are presented based on continuous models to solve the multilinear tensor equation. However, these existing discrete models all depend on ...
A new computational model of the brain based closely on its biology and physiology not only learned a simple visual category learning task exactly as well as lab animals, but even enabled the ...
The proliferation of open-sourced Large Language Models (LLMs) and diverse downstream tasks necessitates efficient model selection, given the impracticality of fine-tuning all candidates due to ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback