41 citations · 152 across the 18 of their papers we have counts for
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cs.LG2016★ 17 cited
Feedforward Initialization for Fast Inference of Deep Generative Networks is biologically plausible
Yoshua Bengio, Benjamin Scellier, Olexa Bilaniuk +2
We consider deep multi-layered generative models such as Boltzmann machines or Hopfield nets in which computation (which implements inference) is both recurrent and stochastic, but…
cs.LG2016★ 15 cited
Equilibrium Propagation: Bridging the Gap Between Energy-Based Models and Backpropagation
Benjamin Scellier, Yoshua Bengio
We introduce Equilibrium Propagation, a learning framework for energy-based models. It involves only one kind of neural computation, performed in both the first phase (when the pre…