XL, dynamic interest modeling, and distributed stream computing to analyze large-scale e-commerce user behavior. By improving long-sequence prediction, real-time processing, and behavioral clustering, ...

Researchers have developed a new forecasting model that helps companies more accurately estimate how many customers are interested in a product -- even when key data is missing. The study introduces a ...

Researchers from Carnegie Mellon University and Los Alamos National Laboratory have used machine learning to create a model that can simulate reactive processes in a diverse set of organic materials ...

Raindrops form inside clouds when tiny particles of water collide and stick together, forming larger droplets that eventually ...

In building LLM applications, enterprises often have to create very long system prompts to adjust the model’s behavior for their applications. These prompts contain company knowledge, preferences, and ...

These local LLMs are changing the game in lots of fun ways.

Using tumor growth modeling and informed neural networks as early predictive clinical endpoints. 2007 Continuous dispersion for invasive motility. 2009 Invasive growth with cell density and oxygen.

Researchers have used machine learning to create a model that simulates reactive processes in organic materials and conditions. Researchers from Carnegie Mellon University and Los Alamos National ...