• Linear Antisymmetric Recurrent Neural Networks 

      Moe, Signe; Remonato, Filippo; Grøtli, Esten Ingar; Gravdahl, Jan Tommy (Peer reviewed; Journal article, 2020)
      Recurrent Neural Networks (RNNs) have a form of memory where the output from a node at one timestep is fed back as input the next timestep in addition to data from the previous layer. This makes them highly suitable for ...