Arousal fluctuates continuously during wakefulness, yet how these moment-to-moment variations shape large-scale functional connectivity (FC) remains unclear. Here, we combined 7T fMRI with concurrent ...

Carey Business School experts Ritu Agarwal and Rick Smith share insights ahead of the latest installment of the Hopkins Forum, a conversation about AI and labor on Feb. 25 ...

Objectives The optimal maternal age at childbirth has been a topic of bourgeoning literature, with earlier ages offering physiological benefits for maternal recovery. In contrast, later ages to give ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Abstract: Q-learning and double Q-learning are well-known sample-based, off-policy reinforcement learning algorithms. However, Q-learning suffers from overestimation bias, while double Q-learning ...

Lab-grown “reductionist replicas” of the human brain are helping scientists understand fetal development and cognitive disorders, including autism. But ethical questions loom. Brain organoids, which ...

Deep learning is at the core of the large language models used by OpenAI's ChatGPT and Microsoft Copilot, for example. More specialized deep learning models have supported a wide range of scientific ...

The same is true for Q# callables defined in Jupyter notebook using the %%qsharp cell magic: These callables can then be invoked as normal Python functions, which will run them in the Q# simulator ...

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

A high-fidelity Python implementation of the Q-learning oligopoly simulation from Calvano et al. (2020). This project provides a complete, tested, and extensible reproduction of the seminal study ...