3 code implementations • 23 May 2019 • Théo Galy-Fajou, Florian Wenzel, Christian Donner, Manfred Opper
We propose a new scalable multi-class Gaussian process classification approach building on a novel modified softmax likelihood function.
1 code implementation • Journal of Machine Learning Research 2018 • Christian Donner, Manfred Opper
We present an approximate Bayesian inference approach for estimating the intensity of an inhomogeneous Poisson process, where the intensity function is modelled using a Gaussian process (GP) prior via a sigmoid link function.
no code implementations • 29 May 2018 • Christian Donner, Manfred Opper
We reconsider a nonparametric density model based on Gaussian processes.
1 code implementation • 4 Sep 2017 • Christian Donner, Manfred Opper
For data which are simulated from a more biologically plausible network with spiking neurons, we show that the Ising model captures well the low order statistics of the data and how the Ising couplings are related to the underlying synaptic structure of the simulated network.