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stat.ML2022
Dynamic mean field programming
George Stamatescu
A dynamic mean field theory is developed for finite state and action Bayesian reinforcement learning in the large state space limit. In an analogy with statistical physics, the Bel…
stat.ML2019★ 4 cited
Critical initialisation in continuous approximations of binary neural networks
George Stamatescu, Federica Gerace, Carlo Lucibello +2
The training of stochastic neural network models with binary () weights and activations via continuous surrogate networks is investigated. We derive new surrogates using a no…