Henderson, Paul M, and Christoph Lampert. “Unsupervised Object-Centric Video Generation and Decomposition in 3D.” In 34th Conference on Neural Information Processing Systems, 33:3106–3117. Curran Associates, 2020.

Henderson, Paul M, and Vittorio Ferrari. “Learning Single-Image 3D Reconstruction by Generative Modelling of Shape, Pose and Shading.”https://doi.org/10.1007/s11263-019-01219-8__International Journal of Computer Vision. Springer Nature, 2020.https://doi.org/10.1007/s11263-019-01219-8 .

Royer, Amélie, and Christoph Lampert. “Localizing Grouped Instances for Efficient Detection in Low-Resource Scenarios.”https://doi.org/10.1109/WACV45572.2020.9093288__In IEEE Winter Conference on Applications of Computer Vision. IEEE, 2020.https://doi.org/10.1109/WACV45572.2020.9093288 .

Royer, Amélie, and Christoph Lampert. “A Flexible Selection Scheme for Minimum-Effort Transfer Learning.”https://doi.org/10.1109/WACV45572.2020.9093635__In 2020 IEEE Winter Conference on Applications of Computer Vision. IEEE, 2020.https://doi.org/10.1109/WACV45572.2020.9093635 .

Royer, Amélie, Konstantinos Bousmalis, Stephan Gouws, Fred Bertsch, Inbar Mosseri, Forrester Cole, and Kevin Murphy. “XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings.”https://doi.org/10.1007/978-3-030-30671-7_3__In Domain Adaptation for Visual Understanding, edited by Richa Singh, Mayank Vatsa, Vishal M. Patel, and Nalini Ratha, 33–49. Springer Nature, 2020.https://doi.org/10.1007/978-3-030-30671-7_3 .

Phuong, Mary, and Christoph Lampert. “Functional vs. Parametric Equivalence of ReLU Networks.” In 8th International Conference on Learning Representations, 2020.

Konstantinov, Nikola H, Elias Frantar, Dan-Adrian Alistarh, and Christoph Lampert. “On the Sample Complexity of Adversarial Multi-Source PAC Learning.” In Proceedings of the 37th International Conference on Machine Learning, 119:5416–25. ML Research Press, 2020.

Royer, Amélie. “Leveraging Structure in Computer Vision Tasks for Flexible Deep Learning Models.”https://doi.org/10.15479/AT:ISTA:8390__Institute of Science and Technology Austria, 2020.https://doi.org/10.15479/AT:ISTA:8390 .

Henderson, Paul M, Vagia Tsiminaki, and Christoph Lampert. “Leveraging 2D Data to Learn Textured 3D Mesh Generation.”https://doi.org/10.1109/CVPR42600.2020.00752__In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 7498–7507. IEEE, 2020.https://doi.org/10.1109/CVPR42600.2020.00752 .

Sun, Rémy, and Christoph Lampert. “KS(Conf): A Light-Weight Test If a Multiclass Classifier Operates Outside of Its Specifications.”https://doi.org/10.1007/s11263-019-01232-x__International Journal of Computer Vision. Springer Nature, 2020.https://doi.org/10.1007/s11263-019-01232-x .

Kersting, Kristian, Christoph Lampert, and Constantin Rothkopf, eds. Wie Maschinen Lernen: Künstliche Intelligenz Verständlich Erklärt. 1st ed. Wiesbaden: Springer Nature, 2019.https://doi.org/10.1007/978-3-658-26763-6 .

Ashok, Pranav, Tomás Brázdil, Krishnendu Chatterjee, Jan Ketínský, Christoph Lampert, and Viktor Toman. “Strategy Representation by Decision Trees with Linear Classifiers.”https://doi.org/10.1007/978-3-030-30281-8_7__In 16th International Conference on Quantitative Evaluation of Systems, 11785:109–28. Springer Nature, 2019.https://doi.org/10.1007/978-3-030-30281-8_7 .

Xian, Yongqin, Christoph Lampert, Bernt Schiele, and Zeynep Akata. “Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly.”https://doi.org/10.1109/tpami.2018.2857768__IEEE Transactions on Pattern Analysis and Machine Intelligence. Institute of Electrical and Electronics Engineers (IEEE), 2019.https://doi.org/10.1109/tpami.2018.2857768 .

Phuong, Mary, and Christoph Lampert. “Distillation-Based Training for Multi-Exit Architectures.”https://doi.org/10.1109/ICCV.2019.00144__In IEEE International Conference on Computer Vision, 2019–October:1355–64. IEEE, 2019.https://doi.org/10.1109/ICCV.2019.00144 .

Kolesnikov, Alexander, Alina Kuznetsova, Christoph Lampert, and Vittorio Ferrari. “Detecting Visual Relationships Using Box Attention.”https://doi.org/10.1109/ICCVW.2019.00217__In Proceedings of the 2019 International Conference on Computer Vision Workshop. IEEE, 2019.https://doi.org/10.1109/ICCVW.2019.00217 .

Phuong, Mary, and Christoph Lampert. “Towards Understanding Knowledge Distillation.” In Proceedings of the 36th International Conference on Machine Learning, 97:5142–51. ML Research Press, 2019.

Konstantinov, Nikola H, and Christoph Lampert. “Robust Learning from Untrusted Sources.” In Proceedings of the 36th International Conference on Machine Learning, 97:3488–98. ML Research Press, 2019.

Sun, Rémy, and Christoph Lampert. “KS(Conf): A Light-Weight Test If a ConvNet Operates Outside of Its Specifications,”https://doi.org/10.1007/978-3-030-12939-2_18__11269:244–59. Springer Nature, 2019.https://doi.org/10.1007/978-3-030-12939-2_18 .

Zimin, Alexander. “Learning from Dependent Data.”https://doi.org/10.15479/AT:ISTA:TH1048__Institute of Science and Technology Austria, 2018.https://doi.org/10.15479/AT:ISTA:TH1048 .

Kolesnikov, Alexander. “Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images.”https://doi.org/10.15479/AT:ISTA:th_1021__Institute of Science and Technology Austria, 2018.https://doi.org/10.15479/AT:ISTA:th_1021 .