首页|New Findings from Southwest Jiaotong University in the Area of Boltzmann Machine s Described (Self-supervised Gaussian Restricted Boltzmann Machine Via Joint Con trastive Representation and Contrastive Divergence)
New Findings from Southwest Jiaotong University in the Area of Boltzmann Machine s Described (Self-supervised Gaussian Restricted Boltzmann Machine Via Joint Con trastive Representation and Contrastive Divergence)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Bo ltzmann Machines. According to news reportingoriginating from Chengdu, People’s Republic of China, by NewsRx correspondents, research stated, “Inthis paper, w e propose a novel self-supervised Gaussian Restricted Boltzmann Machine with con trastivelearning (CL-GRBM), which fuses contrastive representation learning and contrastive divergence to optimizeand enhance the representation of GRBM. Buil t upon the concept of contrastive representation learning,CL-GRBM aims to enhan ce the representation capacity of the GRBM.”
ChengduPeople’s Republic of ChinaAsi aBoltzmann MachinesBoltzmann MachineEmerging TechnologiesMachine Learnin gSouthwest Jiaotong University
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