Building the systems that make large-scale learning practical.
Dean works on the systems and algorithms behind large-scale machine learning. These papers connect distributed training infrastructure with sparse models and large research collaborations. The recurring question is how to make ambitious learning systems practical to build and run.
10 papers
Selected research in language models, generative models. Read the full paper, including the methods, experiments, and reported results.
Paper & contextSelected research in machine learning, efficient ai. Read the full paper, including the methods, experiments, and reported results.
Paper & contextSparsely gated mixture-of-experts layers explore conditional computation using a learned routing network.
Paper & contextSelected research in efficient ai. Read the full paper, including the methods, experiments, and reported results.
Paper & contextSelected research in efficient ai. Read the full paper, including the methods, experiments, and reported results.
Paper & contextSelected research in efficient ai. Read the full paper, including the methods, experiments, and reported results.
Paper & contextSelected research in ai for science, reinforcement learning. Read the full paper, including the methods, experiments, and reported results.
Paper & contextSelected research in ai for science, efficient ai. Read the full paper, including the methods, experiments, and reported results.
Paper & contextSelected research in efficient ai. Read the full paper, including the methods, experiments, and reported results.
Paper & contextSelected research in efficient ai. Read the full paper, including the methods, experiments, and reported results.
Paper & contextAn independent editorial profile. Inclusion does not imply Council membership or endorsement. Research is collaborative; coauthorship does not imply sole credit.
Selection & sources