Christina Göpfert

Publication Activity (10 Years)

Years Active: 2016-2022
Publications (10 Years): 25

Top Topics

Linear Classifiers

Feature Relevance

Recommender Systems

Top Venues

Publications

Benjamin Paaßen, Christina Göpfert, Niels Pinkwart
Faster Confidence Intervals for Item Response Theory via an Approximate Likelihood Profile. EDM (2022)
Michiel Straat, Fthi Abadi, Zhuoyun Kan, Christina Göpfert, Barbara Hammer, Michael Biehl
Supervised learning in the presence of concept drift: a modelling framework. Neural Comput. Appl. 34 (1) (2022)
Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier
Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. WWW (2022)
Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier
Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. CoRR (2022)
Niklas Risse, Christina Göpfert, Jan Philip Göpfert
How to Compare Adversarial Robustness of Classifiers from a Global Perspective. ICANN (1) (2021)
Michiel Straat, Fthi Abadi, Zhuoyun Kan, Christina Göpfert, Barbara Hammer, Michael Biehl
Supervised Learning in the Presence of Concept Drift: A modelling framework. CoRR (2020)
Niklas Risse, Christina Göpfert, Jan Philip Göpfert
Adversarial examples and where to find them. CoRR (2020)
Johannes Brinkrolf, Christina Göpfert, Barbara Hammer
Differential privacy for learning vector quantization. Neurocomputing 342 (2019)
Christina Göpfert, Jan Philip Göpfert, Barbara Hammer
Adversarial Robustness Curves. PKDD/ECML Workshops (1) (2019)
Christina Göpfert, Jan Philip Göpfert, Barbara Hammer
Adversarial Robustness Curves. CoRR (2019)
Michael Biehl, Fthi Abadi, Christina Göpfert, Barbara Hammer
Prototype-based classifiers in the presence of concept drift: A modelling framework. CoRR (2019)
Lukas Pfannschmidt, Christina Göpfert, Ursula Neumann, Dominik Heider, Barbara Hammer
FRI-Feature Relevance Intervals for Interpretable and Interactive Data Exploration. CIBCB (2019)
Michael Biehl, Fthi Abadi, Christina Göpfert, Barbara Hammer
Prototype-Based Classifiers in the Presence of Concept Drift: A Modelling Framework. WSOM+ (2019)
Christina Göpfert, Shai Ben-David, Olivier Bousquet, Sylvain Gelly, Ilya O. Tolstikhin, Ruth Urner
When can unlabeled data improve the learning rate? CoRR (2019)
Lukas Pfannschmidt, Christina Göpfert, Ursula Neumann, Dominik Heider, Barbara Hammer
FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration. CoRR (2019)
Christina Göpfert, Shai Ben-David, Olivier Bousquet, Sylvain Gelly, Ilya O. Tolstikhin, Ruth Urner
When can unlabeled data improve the learning rate? COLT (2019)
Benjamin Paaßen, Christina Göpfert, Barbara Hammer
Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces. Neural Process. Lett. 48 (2) (2018)
Michiel Straat, Fthi Abadi, Christina Göpfert, Barbara Hammer, Michael Biehl
Statistical Mechanics of On-Line Learning Under Concept Drift. Entropy 20 (10) (2018)
Christina Göpfert, Lukas Pfannschmidt, Jan Philip Göpfert, Barbara Hammer
Interpretation of linear classifiers by means of feature relevance bounds. Neurocomputing 298 (2018)
Benjamin Paaßen, Christina Göpfert, Barbara Hammer
Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces. CoRR (2017)
Jan Philip Göpfert, Christina Göpfert, Mario Botsch, Barbara Hammer
Effects of variability in synthetic training data on convolutional neural networks for 3D head reconstruction. SSCI (2017)
Christina Göpfert, Lukas Pfannschmidt, Barbara Hammer
Feature Relevance Bounds for Linear Classification. ESANN (2017)
Benjamin Paassen, Christina Göpfert, Barbara Hammer
Gaussian process prediction for time series of structured data. ESANN (2016)
Johannes Kummert, Benjamin Paassen, Joris Jensen, Christina Göpfert, Barbara Hammer
Local Reject Option for Deterministic Multi-class SVM. ICANN (2) (2016)
Christina Göpfert, Benjamin Paassen, Barbara Hammer
Convergence of Multi-pass Large Margin Nearest Neighbor Metric Learning. ICANN (1) (2016)