CGSchNet, a fast machine-learned model, simulates proteins with high accuracy, enabling drug discovery and protein engineering for cancer treatment. Operating significantly faster than traditional all ...

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 ...

Nvidia Corp. today announced the release of new tools for developers working on artificial intelligence-enabled robots, including humanoids, that enable faster development cycles using simulation, ...

Researchers from Radical AI have published a paper describing TorchSim, a next-generation open-source atomistic simulation ...

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...

AI, Machine Learning & Robotics research at Drexel University's College of Computing & Informatics (CCI) explores algorithms, mathematics, and applications of artificial intelligence (AI) through ...

Their study is centred around answering three research questions: Do ANNs perform better than the traditional multiple regression models in the prediction of lighting parameters and energy demand of ...

In a breakthrough for artificial intelligence (AI) and finance, computer scientists from Texas A&M University have developed a machine learning based method called Symbolic Modeling to handle ...