首页|New Findings from Lawrence Livermore National Laboratory Describe Advances in Ma chine Learning (Machine Learning Assisted Bayesian Inference of Mix and Hot-spot Conditions In Nif Implosions)
New Findings from Lawrence Livermore National Laboratory Describe Advances in Ma chine Learning (Machine Learning Assisted Bayesian Inference of Mix and Hot-spot Conditions In Nif Implosions)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News - A new study on Machine Learning is now available. According to news reporting from Livermore, California, by NewsRx journalists, research stated, “Experiments on the National Ignition Facility (NIF) have provi ded clear evidence of ablator material mixing into the Hot-Spot, leading to degr aded performance. However, inferring the amount of mix and Hot-Spot conditions f rom typical experimental observations (e.g. x-ray spectra and images) is highly challenging.” Financial supporters for this research include LLNL, Laboratory Directed Researc h and Development (LDRD).
LivermoreCaliforniaUnited StatesNo rth and Central AmericaBayesian InferenceCyborgsEmerging TechnologiesMac hine LearningLawrence Livermore National Laboratory
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