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114 Publications

2021 | Preprint | IST-REx-ID: 10803 | OA
Konstantinov, Nikola H., and Christoph Lampert. “Fairness through Regularization for Learning to Rank.” ArXiv, 2102.05996, doi:10.48550/arXiv.2102.05996.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2021 | Thesis | IST-REx-ID: 9418 | OA
Phuong, Mary. Underspecification in Deep Learning. Institute of Science and Technology Austria, 2021, doi:10.15479/AT:ISTA:9418.
[Published Version] View | Files available | DOI
 
2021 | Book Chapter | IST-REx-ID: 14987
Lampert, Christoph. “Zero-Shot Learning.” Computer Vision, edited by Katsushi Ikeuchi, 2nd ed., Springer, 2021, pp. 1395–97, doi:10.1007/978-3-030-63416-2_874.
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2020 | Preprint | IST-REx-ID: 8063 | OA
Anciukevicius, Titas, et al. “Object-Centric Image Generation with Factored Depths, Locations, and Appearances.” ArXiv, 2004.00642.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2020 | Conference Paper | IST-REx-ID: 8188 | OA
Henderson, Paul M., and Christoph Lampert. “Unsupervised Object-Centric Video Generation and Decomposition in 3D.” 34th Conference on Neural Information Processing Systems, vol. 33, Curran Associates, 2020, pp. 3106–3117.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2020 | Journal Article | IST-REx-ID: 6952 | OA
Henderson, Paul M., and Vittorio Ferrari. “Learning Single-Image 3D Reconstruction by Generative Modelling of Shape, Pose and Shading.” International Journal of Computer Vision, vol. 128, Springer Nature, 2020, pp. 835–54, doi:10.1007/s11263-019-01219-8.
[Published Version] View | Files available | DOI | WoS | arXiv
 
2020 | Conference Paper | IST-REx-ID: 7936 | OA
Royer, Amélie, and Christoph Lampert. “Localizing Grouped Instances for Efficient Detection in Low-Resource Scenarios.” IEEE Winter Conference on Applications of Computer Vision, 1716–1725, IEEE, 2020, doi:10.1109/WACV45572.2020.9093288.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2020 | Conference Paper | IST-REx-ID: 7937 | OA
Royer, Amélie, and Christoph Lampert. “A Flexible Selection Scheme for Minimum-Effort Transfer Learning.” 2020 IEEE Winter Conference on Applications of Computer Vision, 2180–2189, IEEE, 2020, doi:10.1109/WACV45572.2020.9093635.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2020 | Book Chapter | IST-REx-ID: 8092 | OA
Royer, Amélie, et al. “XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings.” Domain Adaptation for Visual Understanding, edited by Richa Singh et al., Springer Nature, 2020, pp. 33–49, doi:10.1007/978-3-030-30671-7_3.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2020 | Conference Paper | IST-REx-ID: 7481 | OA
Phuong, Mary, and Christoph Lampert. “Functional vs. Parametric Equivalence of ReLU Networks.” 8th International Conference on Learning Representations, 2020.
[Published Version] View | Files available
 
2020 | Conference Paper | IST-REx-ID: 8724 | OA
Konstantinov, Nikola H., et al. “On the Sample Complexity of Adversarial Multi-Source PAC Learning.” Proceedings of the 37th International Conference on Machine Learning, vol. 119, ML Research Press, 2020, pp. 5416–25.
[Published Version] View | Files available | arXiv
 
2020 | Thesis | IST-REx-ID: 8390 | OA
Royer, Amélie. Leveraging Structure in Computer Vision Tasks for Flexible Deep Learning Models. Institute of Science and Technology Austria, 2020, doi:10.15479/AT:ISTA:8390.
[Published Version] View | Files available | DOI
 
2020 | Conference Paper | IST-REx-ID: 8186 | OA
Henderson, Paul M., et al. “Leveraging 2D Data to Learn Textured 3D Mesh Generation.” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2020, pp. 7498–507, doi:10.1109/CVPR42600.2020.00752.
[Submitted Version] View | Files available | DOI | Download Submitted Version (ext.) | arXiv
 
2020 | Journal Article | IST-REx-ID: 6944 | OA
Sun, Rémy, and Christoph Lampert. “KS(Conf): A Light-Weight Test If a Multiclass Classifier Operates Outside of Its Specifications.” International Journal of Computer Vision, vol. 128, no. 4, Springer Nature, 2020, pp. 970–95, doi:10.1007/s11263-019-01232-x.
[Published Version] View | Files available | DOI | WoS
 
2019 | Book (Editor) | IST-REx-ID: 7171
Kersting, Kristian, et al., editors. Wie Maschinen Lernen: Künstliche Intelligenz Verständlich Erklärt. 1st ed., Springer Nature, 2019, doi:10.1007/978-3-658-26763-6.
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2019 | Conference Paper | IST-REx-ID: 6942 | OA
Ashok, Pranav, et al. “Strategy Representation by Decision Trees with Linear Classifiers.” 16th International Conference on Quantitative Evaluation of Systems, vol. 11785, Springer Nature, 2019, pp. 109–28, doi:10.1007/978-3-030-30281-8_7.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2019 | Journal Article | IST-REx-ID: 6554 | OA
Xian, Yongqin, et al. “Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly.” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 9, Institute of Electrical and Electronics Engineers (IEEE), 2019, pp. 2251–65, doi:10.1109/tpami.2018.2857768.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2019 | Conference Paper | IST-REx-ID: 7479 | OA
Phuong, Mary, and Christoph Lampert. “Distillation-Based Training for Multi-Exit Architectures.” IEEE International Conference on Computer Vision, vol. 2019–October, IEEE, 2019, pp. 1355–64, doi:10.1109/ICCV.2019.00144.
[Submitted Version] View | Files available | DOI | WoS
 
2019 | Conference Paper | IST-REx-ID: 7640 | OA
Kolesnikov, Alexander, et al. “Detecting Visual Relationships Using Box Attention.” Proceedings of the 2019 International Conference on Computer Vision Workshop, 1749–1753, IEEE, 2019, doi:10.1109/ICCVW.2019.00217.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2019 | Conference Paper | IST-REx-ID: 6569 | OA
Phuong, Mary, and Christoph Lampert. “Towards Understanding Knowledge Distillation.” Proceedings of the 36th International Conference on Machine Learning, vol. 97, ML Research Press, 2019, pp. 5142–51.
[Published Version] View | Files available
 

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