Christina Göpfert

According to our database, Christina Göpfert authored at least 19 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Guiding Information: Supervised Models and their Relationship with Data.

Christina Göpfert

PhD thesis, 2023

2022

Supervised learning in the presence of concept drift: a modelling framework.

Michiel Straat, Fthi Abadi, Zhuoyun Kan, Christina Göpfert, Barbara Hammer, Michael Biehl

Neural Comput. Appl., 2022

Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors.

Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Faster Confidence Intervals for Item Response Theory via an Approximate Likelihood Profile.

Benjamin Paaßen, Christina Göpfert, Niels Pinkwart

Proceedings of the 15th International Conference on Educational Data Mining, 2022

2021

How to Compare Adversarial Robustness of Classifiers from a Global Perspective.

Niklas Risse, Christina Göpfert, Jan Philip Göpfert

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

2020

Adversarial examples and where to find them.

Niklas Risse, Christina Göpfert, Jan Philip Göpfert

CoRR, 2020

2019

Differential privacy for learning vector quantization.

Johannes Brinkrolf, Christina Göpfert, Barbara Hammer

Neurocomputing, 2019

Prototype-Based Classifiers in the Presence of Concept Drift: A Modelling Framework.

Michael Biehl, Fthi Abadi, Christina Göpfert, Barbara Hammer

Proceedings of the Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization, 2019

Adversarial Robustness Curves.

Christina Göpfert, Jan Philip Göpfert, Barbara Hammer

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

When can unlabeled data improve the learning rate?

Christina Göpfert, Shai Ben-David, Olivier Bousquet, Sylvain Gelly, Ilya O. Tolstikhin, Ruth Urner

Proceedings of the Conference on Learning Theory, 2019

FRI-Feature Relevance Intervals for Interpretable and Interactive Data Exploration.

Lukas Pfannschmidt, Christina Göpfert, Ursula Neumann, Dominik Heider, Barbara Hammer

Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2019

2018

Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces.

Benjamin Paaßen, Christina Göpfert, Barbara Hammer

Neural Process. Lett., 2018

Interpretation of linear classifiers by means of feature relevance bounds.

Christina Göpfert, Lukas Pfannschmidt, Jan Philip Göpfert, Barbara Hammer

Neurocomputing, 2018

Statistical Mechanics of On-Line Learning Under Concept Drift.

Michiel Straat, Fthi Abadi, Christina Göpfert, Barbara Hammer, Michael Biehl

Entropy, 2018

2017

Effects of variability in synthetic training data on convolutional neural networks for 3D head reconstruction.

Jan Philip Göpfert, Christina Göpfert, Mario Botsch, Barbara Hammer

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Feature Relevance Bounds for Linear Classification.

Christina Göpfert, Lukas Pfannschmidt, Barbara Hammer

Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

2016

Local Reject Option for Deterministic Multi-class SVM.

Johannes Kummert, Benjamin Paassen, Joris Jensen, Christina Göpfert, Barbara Hammer

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

Convergence of Multi-pass Large Margin Nearest Neighbor Metric Learning.

Christina Göpfert, Benjamin Paassen, Barbara Hammer

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

Gaussian process prediction for time series of structured data.

Benjamin Paassen, Christina Göpfert, Barbara Hammer

Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016