Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...

Many "AI experts" have sprung up in the machine learning space since the advent of ChatGPT and other advanced generative AI constructs late last year, but Dr. James McCaffrey of Microsoft Research is ...

They have managed to build a neural network, use it to solve a tricky problem, and then capture its insights in a relatively simple five-part equation that human scientists can use and understand.

A technical paper titled “Accelerating Defect Predictions in Semiconductors Using Graph Neural Networks” was published by researchers at Purdue University, Indian Institute of Technology (IIT) Madras, ...

On 17 October 2024, Martina Lamberti publicly defended her Ph.D. thesis, "Know the Past to See the Future: Memory and Prediction in In-Vitro Cortical Neurons," at the University of Twente. Her ...

A transfer learning-based graph neural network model using mIF images to predict neoadjuvant immunochemotherapy response in patients with gastrointestinal cancer.

In a study published in August, Yale researchers discovered neural networks that could predict underage drinking behavior and risk. By utilizing functional magnetic resonance imaging, or fMRI, and ...

Physics-informed neural networks are faster and more accurate at predicting space junk trajectories than conventional methods, says Sierra Space. Credit: Alamy Stock Photo Sierra Space says it can ...

Scientists from Tomsk Polytechnic University, together with their colleagues, analyzed various methods of planning experiments to determine the optimal technological parameters of polymer scaffold ...

Economists from HSE University have developed a neural network model that can predict the onset of a short-term stock market crisis with over 83% accuracy, one day in advance. The model performs well ...