ODE DL paper with overview
This paper recieved award at #NeurIPS2018. Main idea: defining a deep residual network as a continuously evolving system & instead of updating the hidden units layer by layer, define their derivative with respect to depth instead.
ArXiV: https://arxiv.org/pdf/1806.07366.pdf
GitHub: https://github.com/rtqichen/torchdiffeq
Overview: https://rkevingibson.github.io/blog/neural-networks-as-ordinary-differential-equations/
#ODE #DL #NeurIPS
This paper recieved award at #NeurIPS2018. Main idea: defining a deep residual network as a continuously evolving system & instead of updating the hidden units layer by layer, define their derivative with respect to depth instead.
ArXiV: https://arxiv.org/pdf/1806.07366.pdf
GitHub: https://github.com/rtqichen/torchdiffeq
Overview: https://rkevingibson.github.io/blog/neural-networks-as-ordinary-differential-equations/
#ODE #DL #NeurIPS
