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114 Publications

2020 | Journal Article | IST-REx-ID: 6952 | OA
Henderson, P. M., & Ferrari, V. (2020). Learning single-image 3D reconstruction by generative modelling of shape, pose and shading. International Journal of Computer Vision. Springer Nature. https://doi.org/10.1007/s11263-019-01219-8
[Published Version] View | Files available | DOI | WoS | arXiv
 
2020 | Conference Paper | IST-REx-ID: 7936 | OA
Royer, A., & Lampert, C. (2020). Localizing grouped instances for efficient detection in low-resource scenarios. In IEEE Winter Conference on Applications of Computer Vision. Snowmass Village, CO, United States: IEEE. https://doi.org/10.1109/WACV45572.2020.9093288
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2020 | Conference Paper | IST-REx-ID: 7937 | OA
Royer, A., & Lampert, C. (2020). A flexible selection scheme for minimum-effort transfer learning. In 2020 IEEE Winter Conference on Applications of Computer Vision. Snowmass Village, CO, United States: IEEE. https://doi.org/10.1109/WACV45572.2020.9093635
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2020 | Book Chapter | IST-REx-ID: 8092 | OA
Royer, A., Bousmalis, K., Gouws, S., Bertsch, F., Mosseri, I., Cole, F., & Murphy, K. (2020). XGAN: Unsupervised image-to-image translation for many-to-many mappings. In R. Singh, M. Vatsa, V. M. Patel, & N. Ratha (Eds.), Domain Adaptation for Visual Understanding (pp. 33–49). Springer Nature. https://doi.org/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, M., & Lampert, C. (2020). Functional vs. parametric equivalence of ReLU networks. In 8th International Conference on Learning Representations. Online.
[Published Version] View | Files available
 
2020 | Conference Paper | IST-REx-ID: 8724 | OA
Konstantinov, N. H., Frantar, E., Alistarh, D.-A., & Lampert, C. (2020). On the sample complexity of adversarial multi-source PAC learning. In Proceedings of the 37th International Conference on Machine Learning (Vol. 119, pp. 5416–5425). Online: ML Research Press.
[Published Version] View | Files available | arXiv
 
2020 | Thesis | IST-REx-ID: 8390 | OA
Royer, A. (2020). Leveraging structure in Computer Vision tasks for flexible Deep Learning models. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:8390
[Published Version] View | Files available | DOI
 
2020 | Conference Paper | IST-REx-ID: 8186 | OA
Henderson, P. M., Tsiminaki, V., & Lampert, C. (2020). Leveraging 2D data to learn textured 3D mesh generation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 7498–7507). Virtual: IEEE. https://doi.org/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, R., & Lampert, C. (2020). KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications. International Journal of Computer Vision. Springer Nature. https://doi.org/10.1007/s11263-019-01232-x
[Published Version] View | Files available | DOI | WoS
 
2019 | Book (Editor) | IST-REx-ID: 7171
Kersting, K., Lampert, C., & Rothkopf, C. (Eds.). (2019). Wie Maschinen Lernen: Künstliche Intelligenz Verständlich Erklärt (1st ed.). Wiesbaden: Springer Nature. https://doi.org/10.1007/978-3-658-26763-6
View | Files available | DOI
 
2019 | Conference Paper | IST-REx-ID: 6942 | OA
Ashok, P., Brázdil, T., Chatterjee, K., Křetínský, J., Lampert, C., & Toman, V. (2019). Strategy representation by decision trees with linear classifiers. In 16th International Conference on Quantitative Evaluation of Systems (Vol. 11785, pp. 109–128). Glasgow, United Kingdom: Springer Nature. https://doi.org/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, Y., Lampert, C., Schiele, B., & Akata, Z. (2019). Zero-shot learning - A comprehensive evaluation of the good, the bad and the ugly. IEEE Transactions on Pattern Analysis and Machine Intelligence. Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/tpami.2018.2857768
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2019 | Conference Paper | IST-REx-ID: 7479 | OA
Phuong, M., & Lampert, C. (2019). Distillation-based training for multi-exit architectures. In IEEE International Conference on Computer Vision (Vol. 2019–October, pp. 1355–1364). Seoul, Korea: IEEE. https://doi.org/10.1109/ICCV.2019.00144
[Submitted Version] View | Files available | DOI | WoS
 
2019 | Conference Paper | IST-REx-ID: 7640 | OA
Kolesnikov, A., Kuznetsova, A., Lampert, C., & Ferrari, V. (2019). Detecting visual relationships using box attention. In Proceedings of the 2019 International Conference on Computer Vision Workshop. Seoul, South Korea: IEEE. https://doi.org/10.1109/ICCVW.2019.00217
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2019 | Conference Paper | IST-REx-ID: 6569 | OA
Phuong, M., & Lampert, C. (2019). Towards understanding knowledge distillation. In Proceedings of the 36th International Conference on Machine Learning (Vol. 97, pp. 5142–5151). Long Beach, CA, United States: ML Research Press.
[Published Version] View | Files available
 
2019 | Conference Paper | IST-REx-ID: 6590 | OA
Konstantinov, N. H., & Lampert, C. (2019). Robust learning from untrusted sources. In Proceedings of the 36th International Conference on Machine Learning (Vol. 97, pp. 3488–3498). Long Beach, CA, USA: ML Research Press.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2019 | Conference Paper | IST-REx-ID: 6482 | OA
Sun, R., & Lampert, C. (2019). KS(conf): A light-weight test if a ConvNet operates outside of Its specifications (Vol. 11269, pp. 244–259). Presented at the GCPR: Conference on Pattern Recognition, Stuttgart, Germany: Springer Nature. https://doi.org/10.1007/978-3-030-12939-2_18
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2018 | Thesis | IST-REx-ID: 68 | OA
Zimin, A. (2018). Learning from dependent data. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:TH1048
[Published Version] View | Files available | DOI
 
2018 | Thesis | IST-REx-ID: 197 | OA
Kolesnikov, A. (2018). Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th_1021
[Published Version] View | Files available | DOI
 
2018 | Journal Article | IST-REx-ID: 563 | OA
Ringbauer, H., Kolesnikov, A., Field, D., & Barton, N. H. (2018). Estimating barriers to gene flow from distorted isolation-by-distance patterns. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.117.300638
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS
 

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