Apr 29, 2021 · Neural ODE Processes approach the problem of meta-learning for dynamics using a latent variable model, which permits a flexible aggregation of contextual ...
Oct 21, 2023 · Abstract: Neural ODE Processes approach the problem of meta-learning for dynamics using a latent variable model, which permits a flexible ...
Neural ODE Processes approach the problem of meta-learning for dynamics using a latent variable model, which permits a flexible aggregation of contextual ...
The Neural ODE Process model is extended to use additional information within the Learning Using Privileged Information setting, and this extension is ...
Learning using privileged information (LUPI) is a machine learning paradigm where we have access to additional information during training that may not be ...
bjd39/lupi-ndp: Learning using privileged information with ... - GitHub
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Neural ODE Processes approach the problem of meta-learning for dynamics using a latent variable model, which permits a flexible aggregation of contextual ...
Meta-learning using privileged information for dynamics. B Day, A Norcliffe, J Moss, P Liò. arXiv preprint arXiv:2104.14290, 2021. 4, 2021 ; Modular Neural ...
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Meta-learning using privileged information for dynamics [paper]. Ben Day, Alexander Norcliffe, Jacob Moss, Pietro Liò --ICLR 2020 #Learning to Learn and SimDL ...
The paper describes two mechanisms that can be used for significantly accelerating the speed of Student's learning using privileged information: (1) correction ...
Like variBAD, their algorithm conditions the policy on a meta-learned approximate belief. This approximate belief is learned using privileged information during ...