Traffic state estimation (TSE) bifurcates into two main categories, model-driven and data-driven (e.g., machine learning, ML) approaches, while each suffers from either deficient physics or small data ...

We propose the PGDPNet, the first end-to-end deep learning model for explicit geometry diagram parsing. And we construct a large-scale dataset PGDP5K, containing dense and fine-grained annotations of ...

Study in Npj Digital Medicine evaluates COMPOSER, a deep learning model for early sepsis prediction, showing its effectiveness in improving patient care and reducing in-hospital mortality rates.

Embedding a deep-learning model in the known structure of cellular systems yields DCell, ... A global genetic interaction network maps a wiring diagram of cellular function. Science 353, aaf1420 ...

In this project, we have developed a basic CNN model which is used for "Automatic Modulation Classification" using constellation diagrams. Also we have experimented and compared the results obtained ...

The deep learning model outperformed the other models in this measure (0.196 vs 0.135-0.166, selecting the top 1%). In contrast, deep learning did not improve the negative predictive value.

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, ...

Traffic state estimation (TSE) bifurcates into two main categories, model-driven and data-driven (e.g., machine learning, ML) approaches, while each suffers from either deficient physics or small data ...