5 citations · 18 across the 6 of their papers we have counts for
7 papers
Approximate Variational Inference Based on a Finite Sample of Gaussian Latent Variables
Nikolaos Gianniotis, Christoph Schnörr, Christian Molkenthin +1
Variational methods are employed in situations where exact Bayesian inference becomes intractable due to the difficulty in performing certain integrals. Typically, variational meth…
Mixed Variational Inference
Nikolaos Gianniotis
The Laplace approximation has been one of the workhorses of Bayesian inference. It often delivers good approximations in practice despite the fact that it does not strictly take in…
A Spectral Model for Multimodal Redshift Estimation
Sven D. Kugler, Nikolaos Gianniotis, Kai L. Polsterer
We present a physically inspired model for the problem of redshift estimation. Typically, redshift estimation has been treated as a regression problem that takes as input magnitude…
Model-Coupled Autoencoder for Time Series Visualisation
Nikolaos Gianniotis, Sven D. Kügler, Peter Tiňo +1
We present an approach for the visualisation of a set of time series that combines an echo state network with an autoencoder. For each time series in the dataset we train an echo s…
An Explorative Approach for Inspecting Kepler Data
S. D. Kügler, N. Gianniotis, K. L. Polsterer
The Kepler survey has provided a wealth of astrophysical knowledge by continuously monitoring over 150,000 stars. The resulting database contains thousands of examples of known var…
Autoencoding Time Series for Visualisation
Nikolaos Gianniotis, Dennis Kügler, Peter Tino +2
We present an algorithm for the visualisation of time series. To that end we employ echo state networks to convert time series into a suitable vector representation which is capabl…