activity
20062022
most citedBatch and median neural gas

149 citations · 209 across the 22 of their papers we have counts for

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Showing cs.LGShow all

31 papers · 1 filter

cs.LG2021

Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting

Luca Hermes, Barbara Hammer, Malte Schilling

Prediction of movements is essential for successful cooperation with intelligent systems. We propose a model that integrates organized spatial information as given through the movi…

cs.LG20211 cited

Convex optimization for actionable \& plausible counterfactual explanations

André Artelt, Barbara Hammer

Transparency is an essential requirement of machine learning based decision making systems that are deployed in real world. Often, transparency of a given system is achieved by pro…

cs.LG2021

Contrastive Explanations for Explaining Model Adaptations

André Artelt, Fabian Hinder, Valerie Vaquet +2

Many decision making systems deployed in the real world are not static - a phenomenon known as model adaptation takes place over time. The need for transparency and interpretabilit…

cs.LG2021

Evaluating Robustness of Counterfactual Explanations

André Artelt, Valerie Vaquet, Riza Velioglu +4

Transparency is a fundamental requirement for decision making systems when these should be deployed in the real world. It is usually achieved by providing explanations of the syste…

cs.LG20202 cited

Analysis of Drifting Features

Fabian Hinder, Jonathan Jakob, Barbara Hammer

The notion of concept drift refers to the phenomenon that the distribution, which is underlying the observed data, changes over time. We are interested in an identification of thos…

cs.LG2020

Interpretable Locally Adaptive Nearest Neighbors

Jan Philip Göpfert, Heiko Wersing, Barbara Hammer

When training automated systems, it has been shown to be beneficial to adapt the representation of data by learning a problem-specific metric. This metric is global. We extend this…