Plant diseases remain a major threat to food security and agricultural productivity, especially in resource-constrained ...

At its core, deep learning is inspired by a simplified model of how the human brain works by building effective hierarchical representations of complex data. This course will explore applications and ...

Become a Member The center’s faculty seeks active engagement toward building a robust, comprehensive, and scalable solution for an end-to-end deep learning training and model-serving architecture.

Background Coronary artery disease (CAD) is linked to an increased risk of mild cognitive impairment (MCI). Effective and ...

the researchers identified a model that, when coupled with appropriate data augmentation and optimization partner, may help aid in the detection of skin cancer. Using an accessible deep learning ...

We’re developing a deep learning model that should be able to predict the plasma’s behavior in a split second ... When I say “AI Scientist,” I really mean an AI scientific assistant. The literature ...

This study seeks to construct a basic reinforcement learning-based AI-macroeconomic simulator. We use a deep RL (DRL) approach (DDPG) in an RBC macroeconomic model. We set up two learning scenarios, ...

A number of recent works have shown how deep reinforcement learning can be used to study a variety of economic problems, including optimal policy-making, game theory, and bounded rationality. In this ...