75 citations · 145 across the 11 of their papers we have counts for
3 papers · 1 filter
Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics
Daniel Kunin, Javier Sagastuy-Brena, Surya Ganguli +2
Understanding the dynamics of neural network parameters during training is one of the key challenges in building a theoretical foundation for deep learning. A central obstacle is t…
Pruning neural networks without any data by iteratively conserving synaptic flow
Hidenori Tanaka, Daniel Kunin, Daniel L. K. Yamins +1
Pruning the parameters of deep neural networks has generated intense interest due to potential savings in time, memory and energy both during training and at test time. Recent work…
Two Routes to Scalable Credit Assignment without Weight Symmetry
Daniel Kunin, Aran Nayebi, Javier Sagastuy-Brena +3
The neural plausibility of backpropagation has long been disputed, primarily for its use of non-local weight transport the biologically dubious requirement that one neuron inst…