This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

This repository contains the implementation of the paper of paper Deep Reinforcement Learning for Service Function Chain Placement with Graph Attention and Transformer Encoder. In this paper, we ...

Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...

Reinforcement learning (RL) is machine learning (ML) in which the learning system adjusts its behavior to maximize the amount of reward and minimize the amount of punishment it receives over time ...

Graphs and data visualizations are all around us—charting our steps, our election results, our favorite sports teams’ stats, and trends across our world. But too often, people glance at a graph ...

Nearly a century ago, psychologist B.F. Skinner pioneered a controversial school of thought, behaviorism, to explain human and animal behavior. Behaviorism directly inspired modern reinforcement ...

Large Language Models (LLMs) have set new benchmarks in natural language processing, but their tendency for hallucination—generating inaccurate outputs—remains a critical issue for knowledge-intensive ...

In the fast-paced world of healthcare, I’ve learned that creating a positive work environment is essential for both staff well-being and patient care. At the core of both outcomes is fostering a ...