no code implementations • 13 Feb 2024 • Rasmus Kjær Høier, Christopher Zach
The search for "biologically plausible" learning algorithms has converged on the idea of representing gradients as activity differences.
no code implementations • CVPR 2022 • Huu Le, Rasmus Kjær Høier, Che-Tsung Lin, Christopher Zach
We propose a new algorithm for training deep neural networks (DNNs) with binary weights.
no code implementations • 7 May 2020 • Rasmus Kjær Høier, Christopher Zach
In this work we propose lifted regression/reconstruction networks (LRRNs), which combine lifted neural networks with a guaranteed Lipschitz continuity property for the output layer.