Search Results for author:
Found 5 papers, 1 papers with code
Statistical physics, Bayesian inference and neural information processing
Lecture notes from the course given by Professor Sara A. Solla at the Les Houches summer school on "Statistical physics of Machine Learning".
Neuronal architecture extracts statistical temporal patterns
Concretely, we demonstrate that a simple biologically inspired feedforward neuronal model is able to extract information from up to the third order cumulant to perform time series classification.
Path classification by stochastic linear recurrent neural networks
We investigate the functioning of a classifying biological neural network from the perspective of statistical learning theory, modelled, in a simplified setting, as a continuous-time stochastic recurrent neural network (RNN) with identity activation function.
Unfolding recurrence by Green’s functions for optimized reservoir computing
Cortical networks are strongly recurrent, and neurons have intrinsic temporal dynamics.
Unfolding recurrence by Green's functions for optimized reservoir computing
Cortical networks are strongly recurrent, and neurons have intrinsic temporal dynamics.
