Learning Polymorphic Neural ODEs With Time-Evolving Mixture
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DOI: 10.1109/tpami.2022.3145013
Abstract: Neural ordinary differential equations (NODE) present a new way of considering a deep residual network as a continuous structure by layer depth. However, it fails to overcome its representational limits, where it cannot learn all… read more here.
Keywords: neural odes; ode; evolving mixture; time evolving ... See more keywords