Súkeník, Peter, and Christoph Lampert. “Generalization in Multi-Objective Machine Learning.”https://doi.org/10.48550/arXiv.2208.13499__ArXiv, n.d.https://doi.org/10.48550/arXiv.2208.13499 .
LibreCat: https://research-explorer.ista.ac.at/record/12662
DOI: 10.48550/arXiv.2208.13499
arXiv: 2208.13499

Iofinova, Eugenia B, Nikola H Konstantinov, and Christoph Lampert. “FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data.” Transactions on Machine Learning Research. ML Research Press, 2022.
LibreCat: https://research-explorer.ista.ac.at/record/12495
arXiv: 2106.11732

Prach, Bernd, and Christoph Lampert. “Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks.”https://doi.org/10.1007/978-3-031-19803-8_21__In Computer Vision – ECCV 2022, 13681:350–65. Springer Nature, 2022.https://doi.org/10.1007/978-3-031-19803-8_21 .
LibreCat: https://research-explorer.ista.ac.at/record/11839
DOI: 10.1007/978-3-031-19803-8_21
arXiv: 2208.03160

Lampert, Jasmin, and Christoph Lampert. “Overcoming Rare-Language Discrimination in Multi-Lingual Sentiment Analysis.”https://doi.org/10.1109/bigdata52589.2021.9672003__In 2021 IEEE International Conference on Big Data, 5185–92. IEEE, 2022.https://doi.org/10.1109/bigdata52589.2021.9672003 .
LibreCat: https://research-explorer.ista.ac.at/record/10752
DOI: 10.1109/bigdata52589.2021.9672003
WoS: 000800559505036

Tomaszewska, Paulina, and Christoph Lampert. “Lightweight Conditional Model Extrapolation for Streaming Data under Class-Prior Shift.”https://doi.org/10.1109/icpr56361.2022.9956195__In 26th International Conference on Pattern Recognition, 2022:2128–34. Institute of Electrical and Electronics Engineers, 2022.https://doi.org/10.1109/icpr56361.2022.9956195 .
LibreCat: https://research-explorer.ista.ac.at/record/12161
DOI: 10.1109/icpr56361.2022.9956195
WoS: 000897707602018
arXiv: 2206.05181

Iofinova, Eugenia B, Elena-Alexandra Peste, Mark Kurtz, and Dan-Adrian Alistarh. “How Well Do Sparse ImageNet Models Transfer?”https://doi.org/10.1109/cvpr52688.2022.01195__In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 12256–66. Institute of Electrical and Electronics Engineers, 2022.https://doi.org/10.1109/cvpr52688.2022.01195 .
LibreCat: https://research-explorer.ista.ac.at/record/12299
DOI: 10.1109/cvpr52688.2022.01195
WoS: 000870759105034
arXiv: 2111.13445

Konstantinov, Nikola H, and Christoph Lampert. “Fairness-Aware PAC Learning from Corrupted Data.” Journal of Machine Learning Research. ML Research Press, 2022.
LibreCat: https://research-explorer.ista.ac.at/record/10802
arXiv: 2102.06004

Konstantinov, Nikola H, and Christoph Lampert. “On the Impossibility of Fairness-Aware Learning from Corrupted Data.” In Proceedings of Machine Learning Research, 171:59–83. ML Research Press, 2022.
LibreCat: https://research-explorer.ista.ac.at/record/13241
arXiv: 2102.06004

Konstantinov, Nikola H. “Robustness and Fairness in Machine Learning.”https://doi.org/10.15479/at:ista:10799__Institute of Science and Technology Austria, 2022.https://doi.org/10.15479/at:ista:10799 .
LibreCat: https://research-explorer.ista.ac.at/record/10799
DOI: 10.15479/at:ista:10799

Volhejn, Vaclav, and Christoph Lampert. “Does SGD Implicitly Optimize for Smoothness?”https://doi.org/10.1007/978-3-030-71278-5_18__In 42nd German Conference on Pattern Recognition, 12544:246–59. LNCS. Springer, 2021.https://doi.org/10.1007/978-3-030-71278-5_18 .
LibreCat: https://research-explorer.ista.ac.at/record/9210
DOI: 10.1007/978-3-030-71278-5_18

Phuong, Mary, and Christoph Lampert. “The Inductive Bias of ReLU Networks on Orthogonally Separable Data.” In 9th International Conference on Learning Representations, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/9416

Konstantinov, Nikola H, and Christoph Lampert. “Fairness through Regularization for Learning to Rank.”https://doi.org/10.48550/arXiv.2102.05996__ArXiv, n.d.https://doi.org/10.48550/arXiv.2102.05996 .
LibreCat: https://research-explorer.ista.ac.at/record/10803
DOI: 10.48550/arXiv.2102.05996
arXiv: 2102.05996

Phuong, Mary. “Underspecification in Deep Learning.”https://doi.org/10.15479/AT:ISTA:9418__Institute of Science and Technology Austria, 2021.https://doi.org/10.15479/AT:ISTA:9418 .
LibreCat: https://research-explorer.ista.ac.at/record/9418
DOI: 10.15479/AT:ISTA:9418

Lampert, Christoph. “Zero-Shot Learning.”https://doi.org/10.1007/978-3-030-63416-2_874__In Computer Vision, edited by Katsushi Ikeuchi, 2nd ed., 1395–97. Cham: Springer, 2021.https://doi.org/10.1007/978-3-030-63416-2_874 .
LibreCat: https://research-explorer.ista.ac.at/record/14987
DOI: 10.1007/978-3-030-63416-2_874

Anciukevicius, Titas, Christoph Lampert, and Paul M Henderson. “Object-Centric Image Generation with Factored Depths, Locations, and Appearances.” ArXiv, n.d.
LibreCat: https://research-explorer.ista.ac.at/record/8063
arXiv: 2004.00642

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.
LibreCat: https://research-explorer.ista.ac.at/record/8188
arXiv: 2007.06705

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 .
LibreCat: https://research-explorer.ista.ac.at/record/6952
DOI: 10.1007/s11263-019-01219-8
WoS: 000491042100002
arXiv: 1901.06447

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 .
LibreCat: https://research-explorer.ista.ac.at/record/7936
DOI: 10.1109/WACV45572.2020.9093288
arXiv: 2004.12623

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 .
LibreCat: https://research-explorer.ista.ac.at/record/7937
DOI: 10.1109/WACV45572.2020.9093635
arXiv: 2008.11995

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 .
LibreCat: https://research-explorer.ista.ac.at/record/8092
DOI: 10.1007/978-3-030-30671-7_3
arXiv: 1711.05139