79 citations · 340 across the 10 of their papers we have counts for
10 papers
Approximate Bayes learning of stochastic differential equations
Philipp Batz, Andreas Ruttor, Manfred Opper
We introduce a nonparametric approach for estimating drift and diffusion functions in systems of stochastic differential equations from observations of the state vector. Gaussian p…
Variational estimation of the drift for stochastic differential equations from the empirical density
Philipp Batz, Andreas Ruttor, Manfred Opper
We present a method for the nonparametric estimation of the drift function of certain types of stochastic differential equations from the empirical density. It is based on a variat…
Successful attack on permutation-parity-machine-based neural cryptography
Luís F. Seoane, Andreas Ruttor
An algorithm is presented which implements a probabilistic attack on the key-exchange protocol based on permutation parity machines. Instead of imitating the synchronization of the…
Efficient statistical inference for stochastic reaction processes
Andreas Ruttor, Manfred Opper
We address the problem of estimating unknown model parameters and state variables in stochastic reaction processes when only sparse and noisy measurements are available. Using an a…
Neural Synchronization and Cryptography
Andreas Ruttor
Neural networks can synchronize by learning from each other. In the case of discrete weights full synchronization is achieved in a finite number of steps. Additional networks can b…
Dynamics of neural cryptography
Andreas Ruttor, Wolfgang Kinzel, Ido Kanter
Synchronization of neural networks has been used for novel public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchron…