Extreme Learning Machines (ELMs) represent a class of feedforward neural networks distinguished by their rapid learning speed and analytical determination of output weights. Unlike conventional neural ...

The 2024 Nobel Prize in Chemistry was recently granted to David Baker, Demis Hassabis and John M. Jumper, renowned for their pioneering works in protein design.

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 ...

Graph Neural Networks (GNN), a cutting-edge approach in artificial intelligence, can significantly improve computational calculations in heterogeneous catalysis. Researchers have made a groundbreaking ...

Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, multi-hop evidence. Here’s why BFSI leaders should embrace graph-native AI ...

Expect to hear increasing buzz around graph neural network use cases among hyperscalers in the coming year. Behind the scenes, these are already replacing existing recommendation systems and traveling ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Graphs are, quite simply, a universal ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

Compared to other regression techniques, a well-tuned neural network regression system can produce the most accurate prediction model, says Dr. James McCaffrey of Microsoft Research in presenting this ...