Tag "neural networks"

Researchers at HSE University, MISiS National University of Science and Technology, and the Artificial Intelligence Research Institute (AIRI) have developed an enhanced approach to reinforcement learning for neural networks tasked with navigation in three-dimensional environments. By using the attention mechanism, they managed to improve the performance of a graph neural network by 15%. The study results have been published in IEEE Access.

Specialists at HSE Campus in Perm and clinicians at Perm City Clinical Hospital No. 4, have been collaborating to develop a neural network capable of determining the root cause of a stroke. This marks the world's first attempt to create such a system, the developers note.

A group of scientists from the HSE Faculty of Computer Science has conducted a study on the ability of neural networks to detect humour. It turns out that for more reliable recognition, it’s necessary to change the approach to creating datasets on which neural networks are trained. The scientists presented these results at one of the world's most important conferences on natural language processing — EMNLP 2023. 

One of the most popular writers of the last century, John Ronald Reuel Tolkien, was born on January 3^rd. Researchers from HSE University, AIRI and MISSIS have used machine learning to explore the social connections between the characters of his Middle-earth universe. The algorithm managed to create an accurate picture of the social structures and dynamics of the characters' relationships, providing a unique map of interactions in the epic world. The results of the work were published in IEEE Xplore.

Top development teams around the world are trying to create a neural network similar to a curious but bored three-year-old kid. IQ.HSE shares why this approach is necessary and how such methods can bring us closer to creating strong artificial intelligence.

A team of researchers from HSE University, jointly with the Yandex School of Data Analysis and Yandex Cloud, have developed a neural network for anticipating El Niño climate anomalies. The new algorithm enables more precise predictions of changes in the average surface temperature of oceanic waters that can trigger natural disasters in specific regions of the world. At present, the model is capable of predicting El Niño events one and a half years in advance, and the researchers are working towards extending the forecast period to two years.