We present a novel approach to dealing with overfitting in black-box models. It is based on the leverages of the samples, i.e. on the influence that each observation has on the pa...
The present study introduces information-geometricmeasures to analyze neural ring patterns by taking not only the secondorder but also higher-order interactions among neurons into...
We derive solutions for the problem of missing and noisy data in nonlinear timeseries prediction from a probabilistic point of view. We discuss different approximations to the so...
In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation algorithm for a Gaussian mixture model with a Gaussian smoothing prior on the ce...
In response to Rodriguez' recent article (2001) we compare the performance of simple recurrent nets and "Long Short-Term Memory" (LSTM) recurrent nets on context-fr...