Deep reinforcement learning has demonstrated its capability to solve a diverse array of challenging problems, which were not able to solve previously. It has been able to achieve human-level performance in Atari 2600 games and it has shown great p...
Neural seq2seq models are widely used to generate dialogue using variations of RNN Encoder-Decoder architecture with maximum likelihood estimation as objective function. Advances in this architecture include introducing reinforcement learning to t...
Mathematical models for the self-propulsion of articulated bodies in fluids at low Reynolds number can be interpreted geometrically in terms of connections in principal bundles. Visualization of the local curvature of a connection in this context ...
