Christina Göpfert

27 papers A* 2B 3C 1Journal 14Unranked 6

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Discovering Personalized Semantics for Soft Attributes in Recommender Systems Using Concept Activation Vectors. Trans. Recomm. Syst. Christina Göpfert, Alex Haig, Chih-Wei Hsu, Yinlam Chow, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Hubert Pham, Mohammad Ghavamzadeh, Craig Boutilier
2023	—	`—`	Guiding Information: Supervised Models and their Relationship with Data. Christina Göpfert
2022	A*	`conf`	Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. WWW Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier
2022	J	`jnl`	Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. CoRR Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier
2022	B	`conf`	Faster Confidence Intervals for Item Response Theory via an Approximate Likelihood Profile. EDM Benjamin Paaßen, Christina Göpfert, Niels Pinkwart
2022	J	`jnl`	Supervised learning in the presence of concept drift: a modelling framework. Neural Comput. Appl. Michiel Straat, Fthi Abadi, Zhuoyun Kan, Christina Göpfert, Barbara Hammer, Michael Biehl
2021	—	`conf`	How to Compare Adversarial Robustness of Classifiers from a Global Perspective. ICANN (1) Niklas Risse, Christina Göpfert, Jan Philip Göpfert
2020	J	`jnl`	Adversarial examples and where to find them. CoRR Niklas Risse, Christina Göpfert, Jan Philip Göpfert
2020	J	`jnl`	Supervised Learning in the Presence of Concept Drift: A modelling framework. CoRR Michiel Straat, Fthi Abadi, Zhuoyun Kan, Christina Göpfert, Barbara Hammer, Michael Biehl
2019	—	`conf`	Adversarial Robustness Curves. PKDD/ECML Workshops (1) Christina Göpfert, Jan Philip Göpfert, Barbara Hammer
2019	J	`jnl`	Adversarial Robustness Curves. CoRR Christina Göpfert, Jan Philip Göpfert, Barbara Hammer
2019	J	`jnl`	Differential privacy for learning vector quantization. Neurocomputing Johannes Brinkrolf, Christina Göpfert, Barbara Hammer
2019	J	`jnl`	FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration. CoRR Lukas Pfannschmidt, Christina Göpfert, Ursula Neumann, Dominik Heider, Barbara Hammer
2019	C	`conf`	FRI-Feature Relevance Intervals for Interpretable and Interactive Data Exploration. CIBCB Lukas Pfannschmidt, Christina Göpfert, Ursula Neumann, Dominik Heider, Barbara Hammer
2019	—	`conf`	Prototype-Based Classifiers in the Presence of Concept Drift: A Modelling Framework. WSOM+ Michael Biehl, Fthi Abadi, Christina Göpfert, Barbara Hammer
2019	J	`jnl`	Prototype-based classifiers in the presence of concept drift: A modelling framework. CoRR Michael Biehl, Fthi Abadi, Christina Göpfert, Barbara Hammer
2019	A*	`conf`	When can unlabeled data improve the learning rate? COLT Christina Göpfert, Shai Ben-David, Olivier Bousquet, Sylvain Gelly, Ilya O. Tolstikhin, Ruth Urner
2019	J	`jnl`	When can unlabeled data improve the learning rate? CoRR Christina Göpfert, Shai Ben-David, Olivier Bousquet, Sylvain Gelly, Ilya O. Tolstikhin, Ruth Urner
2018	J	`jnl`	Interpretation of linear classifiers by means of feature relevance bounds. Neurocomputing Christina Göpfert, Lukas Pfannschmidt, Jan Philip Göpfert, Barbara Hammer
2018	J	`jnl`	Statistical Mechanics of On-Line Learning Under Concept Drift. Entropy Michiel Straat, Fthi Abadi, Christina Göpfert, Barbara Hammer, Michael Biehl
2018	J	`jnl`	Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces. Neural Process. Lett. Benjamin Paaßen, Christina Göpfert, Barbara Hammer
2017	—	`conf`	Effects of variability in synthetic training data on convolutional neural networks for 3D head reconstruction. SSCI Jan Philip Göpfert, Christina Göpfert, Mario Botsch, Barbara Hammer
2017	B	`conf`	Feature Relevance Bounds for Linear Classification. ESANN Christina Göpfert, Lukas Pfannschmidt, Barbara Hammer
2017	J	`jnl`	Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces. CoRR Benjamin Paaßen, Christina Göpfert, Barbara Hammer
2016	—	`conf`	Convergence of Multi-pass Large Margin Nearest Neighbor Metric Learning. ICANN (1) Christina Göpfert, Benjamin Paassen, Barbara Hammer
2016	B	`conf`	Gaussian process prediction for time series of structured data. ESANN Benjamin Paassen, Christina Göpfert, Barbara Hammer
2016	—	`conf`	Local Reject Option for Deterministic Multi-class SVM. ICANN (2) Johannes Kummert, Benjamin Paassen, Joris Jensen, Christina Göpfert, Barbara Hammer